diff --git a/README.md b/README.md index fc042a78084f76890d023a09cdafcf0f7613f6d6..63b5e3547eae7649a30571d3502a42e5a9202b28 100644 --- a/README.md +++ b/README.md @@ -17,32 +17,39 @@ configs: default: true --- -# BrainPilotBench — task data +# BrainPilotBench v1 — task data -Public data for the BrainPilotBench v1 task collection: 112 runnable tasks across six data categories. -This repository hosts public data for 111 tasks. H1 has a source-only entry because its source agreement prohibits redistribution. +Public data for research tasks in brain science and human behavior. +Agents use these data to develop neural decoders, predict human responses, and analyze relationships between brain measurements. +The [BrainPilotBench source repository](https://github.com/NeuroAIHub/BrainPilotBench/tree/7306cc0b0e8958cc8f84918b68446310d8dbc662) provides task instructions, environments, submission formats, and scoring code. -The collection combines 108 new tasks with four retained v0 tasks. -Agent benchmark results for the 108 additions are not yet available. -Data preparation and fixed-reference checks do not establish Agent research performance. +**112 tasks · 6 data categories · public data for 111 tasks** -## Find a task +> **Agent benchmark results for the 108 new v1 tasks are not yet available.** +> The four retained v0 tasks have separate historical results. Data preparation and fixed-reference checks are not Agent benchmark results. -The Dataset Viewer shows one catalog row per task. It does not combine recordings or behavioral trials into one sample table. +## Explore the tasks -| Data category | Tasks | Directory | +| Data category | Tasks | Research problems | |---|---:|---| -| EEG | 25 | [Browse tasks](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg) | -| Psychology | 76 | [Browse tasks](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology) | -| MRI | 2 | [Browse tasks](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/mri) | -| Connectomics | 1 | [Browse tasks](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/connectomics) | -| Calcium imaging | 1 | [Browse tasks](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/calcium-imaging) | -| Invasive recordings | 7 | [Browse tasks](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/invasive) | +| [EEG](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg) | 25 | Classify motor imagery, evoked responses, sleep stages, and other scalp-EEG conditions. | +| [Psychology](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology) | 76 | Model participants' recorded choices and responses from causal trial history. | +| [MRI](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/mri) | 2 | Predict age from structural MRI and tonic pain from fMRI connectivity. | +| [Connectomics](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/connectomics) | 1 | Compare anatomical connectivity with measured signal propagation in C. elegans. | +| [Calcium imaging](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/calcium-imaging) | 1 | Analyze RSC place-cell activity and decode behavior. | +| [Invasive recordings](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/invasive) | 7 | Decode movement, muscle activity, handwriting, film conditions, and birdsong from invasive neural recordings. | -The [machine-readable catalog](catalog.jsonl) provides task descriptions, metrics, sources, and access status. -The [collection manifest](collection.json) records the collection totals. +Start with [human casino choices](tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md), +[MRI age prediction](tasks/mri/brain-age-mri/README.md), or +[ECoG finger-flexion decoding](tasks/invasive/ieeg-finger-flexion-bciciv4/README.md). +Each task card explains the research question, available data, and evaluation, then links to its full guide. -## Directory layout +The Dataset Viewer displays one row per task. It is a task directory, not a combined table of neural recordings or behavioral trials. +The [catalog](catalog.jsonl) and [collection manifest](collection.json) provide machine-readable entries and counts. + +## Get data for one task + +Each task has one stable location: ```text tasks/// @@ -51,32 +58,27 @@ tasks/// public/ ``` -Each task has one stable directory. Upload dates and storage batches do not define separate benchmark editions. -Native NPY, NPZ, JSONL, MAT, ZIP, and other task formats remain unchanged. -The collection contains 668 public data files, totaling 37,945,533,281 logical bytes. -Private evaluation files, owner mappings, and secret keys are excluded. - -## Use the data +Read the task card and source terms before download. +Use its versioned GitHub guide to install the environment and prepare a workspace. +The task's `data.lock` pins exact HF commits, file sizes, and SHA-256 digests. +Native scientific formats remain unchanged. -Read the task README and its source terms before download. -Use the [BrainPilotBench source checkout](https://github.com/NeuroAIHub/BrainPilotBench/tree/a79bd29f4cb533f63013b9d4bc0b11fba5e66b53) for environments, protocols, and the CLI. -Its data locks bind exact HF commits, byte counts, and SHA-256 digests. -The v1 task collection is on GitHub main. This source snapshot adds the unified download and preparation workflow. -The workflow update is on a separate feature branch, not yet merged into main. No new npm release is available. +Public files are hosted for 111 tasks, including BCI IV-4 and six invasive-recording tasks. +H1 provides [source download and local preparation instructions](tasks/invasive/falcon-h1-reach-grasp/README.md) because its Data Use Agreement prohibits redistribution. +The film task's public package supports Agent preparation. Block-first scoring still requires a trusted evaluator mapping that is not hosted here. +Private evaluation files, owner mappings, and keys are excluded from this data repository. -The task manifests describe public files only. Private evaluation and official source-benchmark scores remain separate. -BCI IV-4 includes the prepared Train/Valid split, not its original evaluation interval. -H1 provides source links and a split/build recipe, not a mirror. -The film task needs its trusted evaluator mapping for block-first scoring. That mapping is not public. +## Versions, source terms, and results -## Versions and source terms +The v1 collection contains 108 new tasks and four retained v0 tasks. +Individual task versions define scientific protocols. HF commit IDs identify data snapshots. +Task cards link to versioned source guides. Directory navigation links use the current `main` tree. -`v1` names the task collection. Individual task versions identify scientific protocols. -HF commit IDs identify immutable storage snapshots. Use commit-pinned links for reproducible downloads. -The directory navigation links use `main`, which can change. - -The [attribution guide](ATTRIBUTION.md) records source-specific notices and prior publication provenance. -No repository-wide license supersedes the source data terms. +The [attribution guide](ATTRIBUTION.md) records source-specific terms and citations. The root LICENSE does not grant an Apache license for all task data. -The migration preserves existing data bytes and scientific splits. -Earlier immutable commit URLs remain part of the publication history. +BCI IV-4 retains its competition source terms. The film package excludes the copyrighted movie. + +The unified access update is under review in [PR #77](https://github.com/NeuroAIHub/BrainPilotBench/pull/77). +Use the linked source snapshot for its documented workflow until that update reaches GitHub main. +The [data preparation record](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/docs/data-preparation.md) separates delivery checks from Agent evaluation. +Earlier immutable data URLs remain available in the publication history. diff --git a/catalog.jsonl b/catalog.jsonl index a84afe4b93202b42e976d3a762d82029c643a0e0..9e81c742963ea2dd781d5626fd10d59446ffbbea 100644 --- a/catalog.jsonl +++ b/catalog.jsonl @@ -1,112 +1,112 @@ -{"access": "hosted_public", "agent_results": "historical_v0_only", "collection": "v1", "data_category": "calcium-imaging", "metric_direction": "See task protocol", "primary_metric": "See task protocol", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/calcium-imaging/neuro-rsc-place-cell/README.md", "public_bytes": 203632523, "public_file_count": 1, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/calcium-imaging/neuro-rsc-place-cell/README.md", "summary": "RSC 位置细胞动态分析——依据 mouse RSC Ca²⁺ imaging + VR belt 行为数据(VRBeltReframe.mat),完成位置细胞筛选/可视化/贝叶斯解码/trial-bin 相关/firing-rate 动态,交 benchmark_summary.json + report.md + 图。", "task_id": "neuro-rsc-place-cell", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/calcium-imaging/neuro-rsc-place-cell/README.md", "task_version": "0.2", "title": "neuro-rsc-place-cell"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "connectomics", "metric_direction": "maximize", "primary_metric": "score", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/connectomics/celegans-structure-function-divergence/README.md", "public_bytes": 1063606, "public_file_count": 3, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/connectomics/celegans-structure-function-divergence/README.md", "summary": "Candidate integration of an analysis task comparing a measured C. elegans signaling atlas with electron-microscopy connectomes. The agent implements a reusable pipeline for edge ranking, binary-topology community alignment, hub agreement, and pharyngeal co-assignment. A separately isolated evaluator checks numerical outputs on held-out reconstructions; only the public reconstruction and task instructions are available during development.", "task_id": "celegans-structure-function-divergence", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/connectomics/celegans-structure-function-divergence/README.md", "task_version": "0.6", "title": "Anatomical Connectivity and Signal Propagation in C. elegans"} -{"access": "hosted_public", "agent_results": "historical_v0_only", "collection": "v1", "data_category": "eeg", "metric_direction": "See task protocol", "primary_metric": "See task protocol", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/bciciv-2a/README.md", "public_bytes": 202714474, "public_file_count": 1, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/bciciv-2a/README.md", "summary": "4-class motor-imagery decoding on BCI Competition IV Dataset 2a (9 subjects, within-subject cross-session: session T for training, session E for blind test). The agent submits a single PyTorch `MIAgentModel` class (no direct reuse of braindecode's prebuilt decoders); the scorer trains and infers per subject, reporting per-subject accuracy and Cohen's kappa with mean_kappa as the primary metric.", "task_id": "bciciv-2a", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/bciciv-2a/README.md", "task_version": "0.2", "title": "bciciv-2a — 4-class Motor Imagery decoding (BCI Competition IV 2a)"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-cvep-thielen2015/README.md", "public_bytes": 119737938, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-cvep-thielen2015/README.md", "summary": "Thielen2015 cVEP; frozen cvep/thielen2015 protocol adapted for public train/valid model validation.", "task_id": "eeg-cvep-thielen2015", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-cvep-thielen2015/README.md", "task_version": "0.1-public-validation", "title": "Thielen2015 cVEP decoding"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-dementia-dice/README.md", "public_bytes": 510942124, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-dementia-dice/README.md", "summary": "DICE dementia diagnosis; frozen dementia_diagnosis/default protocol adapted for public train/valid model validation.", "task_id": "eeg-dementia-dice", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-dementia-dice/README.md", "task_version": "0.1-public-validation", "title": "DICE EEG classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-ern/README.md", "public_bytes": 185087647, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-ern/README.md", "summary": "ERP CORE ERN; frozen ern/default protocol adapted for public train/valid model validation.", "task_id": "eeg-erp-ern", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-erp-ern/README.md", "task_version": "0.1-public-validation", "title": "ERN EEG classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-lrp/README.md", "public_bytes": 185087647, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-lrp/README.md", "summary": "ERP CORE LRP; frozen lrp/default protocol adapted for public train/valid model validation.", "task_id": "eeg-erp-lrp", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-erp-lrp/README.md", "task_version": "0.1-public-validation", "title": "LRP EEG classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-mmn/README.md", "public_bytes": 460888332, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-mmn/README.md", "summary": "ERP CORE MMN; frozen mismatch_negativity/default protocol adapted for public train/valid model validation.", "task_id": "eeg-erp-mmn", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-erp-mmn/README.md", "task_version": "0.1-public-validation", "title": "Mismatch-negativity EEG classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n170/README.md", "public_bytes": 148243682, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n170/README.md", "summary": "ERP CORE N170; frozen n170/default protocol adapted for public train/valid model validation.", "task_id": "eeg-erp-n170", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-erp-n170/README.md", "task_version": "0.1-public-validation", "title": "N170 EEG classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n2pc/README.md", "public_bytes": 148345021, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n2pc/README.md", "summary": "ERP CORE N2pc; frozen n2pc/default protocol adapted for public train/valid model validation.", "task_id": "eeg-erp-n2pc", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-erp-n2pc/README.md", "task_version": "0.1-public-validation", "title": "N2pc EEG classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n400/README.md", "public_bytes": 55590922, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n400/README.md", "summary": "ERP CORE N400; frozen n400/default protocol adapted for public train/valid model validation.", "task_id": "eeg-erp-n400", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-erp-n400/README.md", "task_version": "0.1-public-validation", "title": "N400 EEG classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-p3/README.md", "public_bytes": 92652002, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-p3/README.md", "summary": "ERP CORE P3; frozen p3/kappenman2021p3 protocol adapted for public train/valid model validation.", "task_id": "eeg-erp-p3", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-erp-p3/README.md", "task_version": "0.1-public-validation", "title": "Kappenman2021 P3 EEG classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-me-highgamma2017/README.md", "public_bytes": 2041458389, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-me-highgamma2017/README.md", "summary": "High-Gamma motor execution; frozen motor_execution/schirrmeister2017 protocol adapted for public train/valid model validation.", "task_id": "eeg-me-highgamma2017", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-me-highgamma2017/README.md", "task_version": "0.1-public-validation", "title": "High-Gamma motor-execution classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-me-ofner2017/README.md", "public_bytes": 443100882, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-me-ofner2017/README.md", "summary": "Ofner2017 motor execution; frozen motor_execution/ofner2017 protocol adapted for public train/valid model validation.", "task_id": "eeg-me-ofner2017", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-me-ofner2017/README.md", "task_version": "0.1-public-validation", "title": "Ofner2017 motor-execution classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mental-arithmetic-zyma2019/README.md", "public_bytes": 63605750, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mental-arithmetic-zyma2019/README.md", "summary": "Zyma mental arithmetic; frozen mental_arithmetic/default protocol adapted for public train/valid model validation.", "task_id": "eeg-mental-arithmetic-zyma2019", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-mental-arithmetic-zyma2019/README.md", "task_version": "0.1-public-validation", "title": "Zyma2019 mental-arithmetic classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-barachant2012/README.md", "public_bytes": 11825808, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-barachant2012/README.md", "summary": "AlexMI motor imagery; frozen motor_imagery/barachant2012 protocol adapted for public train/valid model validation.", "task_id": "eeg-mi-barachant2012", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-mi-barachant2012/README.md", "task_version": "0.1-public-validation", "title": "AlexMI motor-imagery classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-bnci2014/README.md", "public_bytes": 170344916, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-bnci2014/README.md", "summary": "BCI-IV-2a native subject-grouped motor-imagery task, shared with AgentEEGBench.", "task_id": "eeg-mi-bnci2014", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-mi-bnci2014/README.md", "task_version": "0.1-public-validation", "title": "BCI-IV-2a native motor-imagery classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-cho2017/README.md", "public_bytes": 1023001442, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-cho2017/README.md", "summary": "Cho2017 motor imagery; frozen motor_imagery/cho2017 protocol adapted for public train/valid model validation.", "task_id": "eeg-mi-cho2017", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-mi-cho2017/README.md", "task_version": "0.1-public-validation", "title": "Cho2017 motor-imagery classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-eegmmidb/README.md", "public_bytes": 929308208, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-eegmmidb/README.md", "summary": "EEGMMIDB motor imagery; frozen motor_imagery/schalk2004bci2000 protocol adapted for public train/valid model validation.", "task_id": "eeg-mi-eegmmidb", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-mi-eegmmidb/README.md", "task_version": "0.1-public-validation", "title": "EEGMMIDB motor-imagery classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-openbmi2019/README.md", "public_bytes": 1024405402, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-openbmi2019/README.md", "summary": "OpenBMI motor imagery; frozen motor_imagery/lee2019mi protocol adapted for public train/valid model validation.", "task_id": "eeg-mi-openbmi2019", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-mi-openbmi2019/README.md", "task_version": "0.1-public-validation", "title": "OpenBMI motor-imagery classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-zhou2016/README.md", "public_bytes": 32355620, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-zhou2016/README.md", "summary": "Zhou2016 motor imagery; frozen motor_imagery/zhou2016 protocol adapted for public train/valid model validation.", "task_id": "eeg-mi-zhou2016", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-mi-zhou2016/README.md", "task_version": "0.1-public-validation", "title": "Zhou2016 motor-imagery classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-p3-openbmi2019/README.md", "public_bytes": 10623665898, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-p3-openbmi2019/README.md", "summary": "OpenBMI P3; frozen p3/lee2019erp protocol adapted for public train/valid model validation.", "task_id": "eeg-p3-openbmi2019", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-p3-openbmi2019/README.md", "task_version": "0.1-public-validation", "title": "OpenBMI P3 EEG classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-sleep-stage-sleepedf/README.md", "public_bytes": 4453124284, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-sleep-stage-sleepedf/README.md", "summary": "Sleep-EDF full native subject-disjoint sleep staging with public train/validation; two EEG channels, 30-second windows, and five-class balanced accuracy.", "task_id": "eeg-sleep-stage-sleepedf", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-sleep-stage-sleepedf/README.md", "task_version": "0.1-public-validation", "title": "Sleep-EDF cassette sleep-stage classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-ssvep-openbmi2019/README.md", "public_bytes": 1024405402, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-ssvep-openbmi2019/README.md", "summary": "OpenBMI SSVEP; frozen ssvep/lee2019ssvep protocol adapted for public train/valid model validation.", "task_id": "eeg-ssvep-openbmi2019", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-ssvep-openbmi2019/README.md", "task_version": "0.1-public-validation", "title": "OpenBMI SSVEP classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-ssvep-wang2017/README.md", "public_bytes": 796760562, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-ssvep-wang2017/README.md", "summary": "Wang2017 SSVEP; frozen ssvep/default protocol adapted for public train/valid model validation.", "task_id": "eeg-ssvep-wang2017", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-ssvep-wang2017/README.md", "task_version": "0.1-public-validation", "title": "Wang2017 SSVEP classification"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-typing-spanishbcbl/README.md", "public_bytes": 3539526604, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-typing-spanishbcbl/README.md", "summary": "SpanishBCBL EEG typing; frozen typing/default protocol adapted for public train/valid model validation.", "task_id": "eeg-typing-spanishbcbl", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-typing-spanishbcbl/README.md", "task_version": "0.1-public-validation", "title": "SpanishBCBL EEG typing classification"} -{"access": "hosted_public", "agent_results": "historical_v0_only", "collection": "v1", "data_category": "eeg", "metric_direction": "See task protocol", "primary_metric": "See task protocol", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/sleep-edf/README.md", "public_bytes": 1225526664, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/sleep-edf/README.md", "summary": "5-class sleep-staging on Sleep-EDF Cassette (20 subjects, single-channel Fpz-Cz EEG, 30 s epochs → Wake / N1 / N2 / N3 / REM). Subjects 0-13 are the training pool, 14-15 are validation, and 16-19 are the private held-out test set. The agent submits a PyTorch `SleepAgentModel` class (no direct reuse of prebuilt sleep-staging models); the scorer trains one shared model with class-weighted CE and early stopping, then blind-tests on subjects 16-19, reporting Cohen's kappa (primary) alongside accuracy / balanced accuracy / macro F1 / per-class recall.", "task_id": "sleep-edf", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/sleep-edf/README.md", "task_version": "0.2", "title": "sleep-edf — 5-class Sleep Staging (Sleep-EDF Cassette)"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "invasive", "metric_direction": "minimize", "primary_metric": "normalized_spectrogram_MSE", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/intracortical/falcon-b1-birdsong/README.md", "public_bytes": 170230855, "public_file_count": 11, "source_url": "https://dandiarchive.org/dandiset/001046/draft", "summary": "Predict a zebra finch vocalization spectrogram from one complete motif of intracortical threshold crossings at a time.", "task_id": "falcon-b1-birdsong", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/invasive/falcon-b1-birdsong/README.md", "task_version": "0.1-public-validation-motif", "title": "B1: birdsong spectrogram"} -{"access": "source_only", "agent_results": "not_yet_available", "collection": "v1", "data_category": "invasive", "metric_direction": "maximize", "primary_metric": "R2_variance_weighted", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/intracortical/falcon-h1-reach-grasp/README.md", "public_bytes": 0, "public_file_count": 0, "source_url": "https://dandiarchive.org/dandiset/000954/draft", "summary": "Develop a causal intracortical decoder for seven attempted arm and grasp velocities, with chronological training and public validation on a later recording date.", "task_id": "falcon-h1-reach-grasp", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/invasive/falcon-h1-reach-grasp/README.md", "task_version": "0.1-public-validation-stream", "title": "H1: attempted reach and grasp"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "invasive", "metric_direction": "minimize", "primary_metric": "WER", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/intracortical/falcon-h2-handwriting/README.md", "public_bytes": 1110017522, "public_file_count": 86, "source_url": "https://dandiarchive.org/dandiset/000950/0.241029.1403", "summary": "Develop a streaming decoder for attempted handwriting from intracortical activity and return one English sentence at each complete trial boundary.", "task_id": "falcon-h2-handwriting", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/invasive/falcon-h2-handwriting/README.md", "task_version": "0.1-public-validation-stream", "title": "H2: attempted handwriting"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "invasive", "metric_direction": "maximize", "primary_metric": "R2_variance_weighted", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/intracortical/falcon-m1-emg/README.md", "public_bytes": 134424422, "public_file_count": 18, "source_url": "https://dandiarchive.org/dandiset/000941/0.241029.1405", "summary": "Develop a causal 64-channel decoder for 16 upper-limb EMG signals. Train on earlier M1-A dates and validate on the final held-in date.", "task_id": "falcon-m1-emg", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/invasive/falcon-m1-emg/README.md", "task_version": "0.1-public-validation-stream", "title": "M1-A: upper-limb EMG"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "invasive", "metric_direction": "maximize", "primary_metric": "R2_variance_weighted", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/intracortical/falcon-m2-finger-velocity/README.md", "public_bytes": 13234392, "public_file_count": 30, "source_url": "https://dandiarchive.org/dandiset/000953/draft", "summary": "Develop a causal 96-channel decoder for two finger-group velocities. Train on earlier M2 dates and validate on the final held-in date.", "task_id": "falcon-m2-finger-velocity", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/invasive/falcon-m2-finger-velocity/README.md", "task_version": "0.1-public-validation-stream", "title": "M2: finger-group velocity"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "invasive", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/ieeg/ieeg-film-speech-music/README.md", "public_bytes": 922341200, "public_file_count": 257, "source_url": "https://doi.org/10.18112/openneuro.ds003688.v1.0.7", "summary": "Predict speech or music from independent clinical iEEG windows in unseen segments of the same film for each participant.", "task_id": "ieeg-film-speech-music", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/invasive/ieeg-film-speech-music/README.md", "task_version": "0.2-complete-guarded-windows", "title": "Film speech versus music from clinical iEEG"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "invasive", "metric_direction": "maximize", "primary_metric": "pearson_r", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/ieeg/ieeg-finger-flexion-bciciv4/README.md", "public_bytes": 324773839, "public_file_count": 14, "source_url": "https://www.bbci.de/competition/iv/", "summary": "Predict five finger-flexion trajectories from human ECoG in three participants, with chronological public validation and a guarded within-participant split.", "task_id": "ieeg-finger-flexion-bciciv4", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/invasive/ieeg-finger-flexion-bciciv4/README.md", "task_version": "0.1-public-validation-offline", "title": "BCI Competition IV Dataset 4: finger flexion"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "mri", "metric_direction": "minimize", "primary_metric": "test_mae", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/mri/brain-age-mri/README.md", "public_bytes": 3729262581, "public_file_count": 1, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/mri/brain-age-mri/README.md", "summary": "Predict chronological age from anonymized T1-weighted structural MRI. Build and freeze a model using 449 public subjects; the evaluator runs the submitted inference entry on 112 held-out images and computes subject-level MAE.", "task_id": "brain-age-mri", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/mri/brain-age-mri/README.md", "task_version": "0.1-candidate", "title": "Age Prediction from Structural MRI"} -{"access": "hosted_public", "agent_results": "historical_v0_only", "collection": "v1", "data_category": "mri", "metric_direction": "See task protocol", "primary_metric": "See task protocol", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/mri/tops-fmri/README.md", "public_bytes": 965667246, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/mri/tops-fmri/README.md", "summary": "用公开 Study3 fMRI dynamic-FC 训练一个 279 ROI / 38781 edge 的**线性** tonic-pain connectivity signature,提交权重 w_raw/b_raw 和 numpy-only apply_signature.py; benchmark 平台**私下**用 Study4/Study5 held-out features + labels 计算 Pearson r / AUC,聚合 0-1 分。agent 无法接触 held-out labels(工作区隔离 + scorer only)。", "task_id": "tops-fmri", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/mri/tops-fmri/README.md", "task_version": "0.1", "title": "tops-fmri — Tonic Pain Signature (linear FC, external validation)"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-badham2017deficits-exp1/README.md", "public_bytes": 2304677, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-badham2017deficits-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for badham2017deficits/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-badham2017deficits-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-badham2017deficits-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Category Learning from Feedback"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-bahrami2020four-exp/README.md", "public_bytes": 5106777, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-bahrami2020four-exp/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for bahrami2020four/exp.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-bahrami2020four-exp", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-bahrami2020four-exp/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Choices Among Four Rewards"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/README.md", "public_bytes": 3027152, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for collsiöö2023MCPL/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-collsioo2023mcpl-exp1-775cd1984f", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Hormone-Level Estimates from Verbal Cues"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/README.md", "public_bytes": 3201056, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for collsiöö2023MCPL/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-collsioo2023mcpl-exp2-6bd18ff5bf", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Hormone-Level Estimates from Numeric Cues"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/README.md", "public_bytes": 2025867, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for collsiöö2023MCPL/exp3.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-collsioo2023mcpl-exp3-c372064286", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Hormone-Level Estimates from Two Cues"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-cox2017information-exp1/README.md", "public_bytes": 8684274, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-cox2017information-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for cox2017information/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-cox2017information-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-cox2017information-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Recognition of Studied Word Pairs"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/README.md", "public_bytes": 8466948, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for enkavi2019adaptivenback/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-enkavi2019adaptivenback-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human N-Back Letter Responses"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019digitspan-exp1/README.md", "public_bytes": 5692403, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019digitspan-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for enkavi2019digitspan/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-enkavi2019digitspan-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-enkavi2019digitspan-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Digit-Sequence Recall"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019gonogo-exp1/README.md", "public_bytes": 7564952, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019gonogo-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for enkavi2019gonogo/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-enkavi2019gonogo-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-enkavi2019gonogo-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Go/No-Go Keypresses"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019recentprobes-exp1/README.md", "public_bytes": 3678382, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019recentprobes-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for enkavi2019recentprobes/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-enkavi2019recentprobes-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-enkavi2019recentprobes-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Recognition of Recent Letters"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-feng2021dynamics-exp1/README.md", "public_bytes": 3114689, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-feng2021dynamics-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for feng2021dynamics/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-feng2021dynamics-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-feng2021dynamics-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Choices Between Changing Slot Machines"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-flesch2018comparing-exp1/README.md", "public_bytes": 31867420, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-flesch2018comparing-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for flesch2018comparing/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-flesch2018comparing-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-flesch2018comparing-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Tree-Category Learning Across Gardens"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-frey2017cct-exp1/README.md", "public_bytes": 71600868, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-frey2017cct-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for frey2017cct/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-frey2017cct-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-frey2017cct-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Stop-or-Continue Card Choices"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-frey2017risk-exp1/README.md", "public_bytes": 12928138, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-frey2017risk-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for frey2017risk/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-frey2017risk-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-frey2017risk-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Balloon Pumping and Stopping"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp1/README.md", "public_bytes": 2951357, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for garcia2023experiential/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-garcia2023experiential-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-garcia2023experiential-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Reward Choices and Odds Estimates — Experiment 1"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp2/README.md", "public_bytes": 2951505, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp2/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for garcia2023experiential/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-garcia2023experiential-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-garcia2023experiential-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Reward Choices and Odds Estimates — Experiment 2"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp3/README.md", "public_bytes": 2917546, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp3/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for garcia2023experiential/exp3.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-garcia2023experiential-exp3", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-garcia2023experiential-exp3/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Reward Choices and Odds Estimates — Experiment 3"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp4/README.md", "public_bytes": 2292628, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp4/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for garcia2023experiential/exp4.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-garcia2023experiential-exp4", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-garcia2023experiential-exp4/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Reward Choices and Odds Estimates — Experiment 4"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2018deconstructing-exp1/README.md", "public_bytes": 319085, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2018deconstructing-exp1/README.md", "summary": "Public-data Agent modeling of gershman2018deconstructing/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-gershman2018deconstructing-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-gershman2018deconstructing-exp1/README.md", "task_version": "0.1-public-validation", "title": "Human Choices Against a Fixed-Zero Slot Machine"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2018deconstructing-exp2/README.md", "public_bytes": 321792, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2018deconstructing-exp2/README.md", "summary": "Public-data Agent modeling of gershman2018deconstructing/exp2.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-gershman2018deconstructing-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-gershman2018deconstructing-exp2/README.md", "task_version": "0.1-public-validation", "title": "Human Choices Between Unequal Slot Machines"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2020reward-exp1/README.md", "public_bytes": 2322153, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2020reward-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for gershman2020reward/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-gershman2020reward-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-gershman2020reward-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Stimulus–Response Learning from Rewards"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-hebart2023things-exp1/README.md", "public_bytes": 156881709, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-hebart2023things-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for hebart2023things/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-hebart2023things-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-hebart2023things-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Odd-One-Out Judgments"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-hilbig2014generalized-exp1/README.md", "public_bytes": 591437, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-hilbig2014generalized-exp1/README.md", "summary": "Public-data Agent modeling of hilbig2014generalized/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-hilbig2014generalized-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-hilbig2014generalized-exp1/README.md", "task_version": "0.1-public-validation", "title": "Human Product Choices from Expert Ratings"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-jansen2021dunningkruger-exp1/README.md", "public_bytes": 31736579, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-jansen2021dunningkruger-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for jansen2021dunningkruger/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-jansen2021dunningkruger-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-jansen2021dunningkruger-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Grammar Quiz Self-Estimates"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2016when-exp1/README.md", "public_bytes": 2813931, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2016when-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for kool2016when/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-kool2016when-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-kool2016when-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Spaceship Choices amid Treasure and Antimatter"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2016when-exp2/README.md", "public_bytes": 4096825, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2016when-exp2/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for kool2016when/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-kool2016when-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-kool2016when-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Spaceship and Alien Choices for Treasure"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2017cost-exp1/README.md", "public_bytes": 3703289, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2017cost-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for kool2017cost/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-kool2017cost-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-kool2017cost-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Spaceship Choices with Treasure Multipliers"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2017cost-exp2/README.md", "public_bytes": 3618680, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2017cost-exp2/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for kool2017cost/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-kool2017cost-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-kool2017cost-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Spaceship and Alien Choices with Multipliers"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-krueger2022identifying-exp1/README.md", "public_bytes": 28635461, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-krueger2022identifying-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for krueger2022identifying/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-krueger2022identifying-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-krueger2022identifying-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Choices Among Six Gambles"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kumar2023disentangling-exp1/README.md", "public_bytes": 42562418, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kumar2023disentangling-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for kumar2023disentangling/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-kumar2023disentangling-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-kumar2023disentangling-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Choices on a Hidden Binary Grid"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md", "public_bytes": 450595, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md", "summary": "Public-data Agent modeling of lefebvre2017behavioural/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-lefebvre2017behavioural-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Choice in a Casino Task"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-lefebvre2017behavioural-exp2/README.md", "public_bytes": 339457, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-lefebvre2017behavioural-exp2/README.md", "summary": "Public-data Agent modeling of lefebvre2017behavioural/exp2.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-lefebvre2017behavioural-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-lefebvre2017behavioural-exp2/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Casino Choices with Gains and Losses"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-levering2020revisiting-exp1/README.md", "public_bytes": 1229159, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-levering2020revisiting-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for levering2020revisiting/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-levering2020revisiting-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-levering2020revisiting-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Object Classification and Typicality Ratings — Experiment 1"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-levering2020revisiting-exp2/README.md", "public_bytes": 995024, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-levering2020revisiting-exp2/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for levering2020revisiting/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-levering2020revisiting-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-levering2020revisiting-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Object Classification and Typicality Ratings — Experiment 2"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp0/README.md", "public_bytes": 2623321, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp0/README.md", "summary": "Public-data Agent modeling of ludwig2023human/exp0.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-ludwig2023human-exp0", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-ludwig2023human-exp0/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Fruit-Market Navigation and Feeding — Experiment 0"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp1/README.md", "public_bytes": 847355, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp1/README.md", "summary": "Public-data Agent modeling of ludwig2023human/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-ludwig2023human-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-ludwig2023human-exp1/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Fruit-Market Navigation and Feeding — Experiment 1"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp2/README.md", "public_bytes": 799996, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp2/README.md", "summary": "Public-data Agent modeling of ludwig2023human/exp2.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-ludwig2023human-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-ludwig2023human-exp2/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Fruit-Market Navigation and Feeding — Experiment 2"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-peterson2021using-exp1/README.md", "public_bytes": 185996551, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-peterson2021using-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for peterson2021using/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-peterson2021using-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-peterson2021using-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Gamble Choices under Varying Feedback"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-plonsky2018when-exp1/README.md", "public_bytes": 14186060, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-plonsky2018when-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for plonsky2018when/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-plonsky2018when-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-plonsky2018when-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Gamble Choices before and after Feedback"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp1/README.md", "public_bytes": 897131, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for popov2023intent/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-popov2023intent-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-popov2023intent-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Word Study and Recall — Experiment 1"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp2/README.md", "public_bytes": 722615, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp2/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for popov2023intent/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-popov2023intent-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-popov2023intent-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Word-Pair Study and Recall"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp3/README.md", "public_bytes": 1081021, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp3/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for popov2023intent/exp3.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-popov2023intent-exp3", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-popov2023intent-exp3/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Word Study and Recall — Experiment 3"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ruggeri2022globalizability-exp1/README.md", "public_bytes": 20495426, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ruggeri2022globalizability-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for ruggeri2022globalizability/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-ruggeri2022globalizability-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-ruggeri2022globalizability-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Preferences for Immediate and Delayed Payments"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/README.md", "public_bytes": 2735477, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for sadeghiyeh2020temporal/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-sadeghiyeh2020temporal-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Slot-Machine Choices Across Games"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp1/README.md", "public_bytes": 1693724, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp1/README.md", "summary": "Public-data Agent modeling of schulz2020finding/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-schulz2020finding-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-schulz2020finding-exp1/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Search Among Eight Reward Options — Experiment 1"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp2/README.md", "public_bytes": 1108447, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp2/README.md", "summary": "Public-data Agent modeling of schulz2020finding/exp2.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-schulz2020finding-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-schulz2020finding-exp2/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Search Among Eight Reward Options — Experiment 2"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp3/README.md", "public_bytes": 1723768, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp3/README.md", "summary": "Public-data Agent modeling of schulz2020finding/exp3.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-schulz2020finding-exp3", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-schulz2020finding-exp3/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Search Among Eight Reward Options — Experiment 3"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp4/README.md", "public_bytes": 1524152, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp4/README.md", "summary": "Public-data Agent modeling of schulz2020finding/exp4.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-schulz2020finding-exp4", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-schulz2020finding-exp4/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Search Among Eight Reward Options — Experiment 4"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp5/README.md", "public_bytes": 2300511, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp5/README.md", "summary": "Public-data Agent modeling of schulz2020finding/exp5.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-schulz2020finding-exp5", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-schulz2020finding-exp5/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Search Among Eight Reward Options — Experiment 5"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-somerville2017charting-exp1/README.md", "public_bytes": 4696596, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-somerville2017charting-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for somerville2017charting/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-somerville2017charting-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-somerville2017charting-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Exploration of Two Slot Machines"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-speekenbrink2008learning-exp1/README.md", "public_bytes": 497343, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-speekenbrink2008learning-exp1/README.md", "summary": "Public-data Agent modeling of speekenbrink2008learning/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-speekenbrink2008learning-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-speekenbrink2008learning-exp1/README.md", "task_version": "0.1-public-validation", "title": "Predicting Human Weather Judgments from Tarot Cards"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp1/README.md", "public_bytes": 2193605, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp1/README.md", "summary": "Public-data Agent modeling of steingroever2015data/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-steingroever2015data-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-steingroever2015data-exp1/README.md", "task_version": "0.1-public-validation", "title": "Human Choices from Four Card Decks — Experiment 1"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp2/README.md", "public_bytes": 66396, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp2/README.md", "summary": "Public-data Agent modeling of steingroever2015data/exp2.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-steingroever2015data-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-steingroever2015data-exp2/README.md", "task_version": "0.1-public-validation", "title": "Human Choices from Four Card Decks — Experiment 2"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp3/README.md", "public_bytes": 681645, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp3/README.md", "summary": "Public-data Agent modeling of steingroever2015data/exp3.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-steingroever2015data-exp3", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-steingroever2015data-exp3/README.md", "task_version": "0.1-public-validation", "title": "Human Choices from Four Card Decks — Experiment 3"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp2/README.md", "public_bytes": 12159394, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp2/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for tomov2020discovery/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-tomov2020discovery-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-tomov2020discovery-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Subway Navigation — Experiment 2"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp4/README.md", "public_bytes": 3021550, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp4/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for tomov2020discovery/exp4.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-tomov2020discovery-exp4", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-tomov2020discovery-exp4/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Subway Navigation — Experiment 4"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp5/README.md", "public_bytes": 12369221, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp5/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for tomov2020discovery/exp5.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-tomov2020discovery-exp5", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-tomov2020discovery-exp5/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Subway Navigation — Experiment 5"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp7/README.md", "public_bytes": 8601475, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp7/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for tomov2020discovery/exp7.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-tomov2020discovery-exp7", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-tomov2020discovery-exp7/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Subway Navigation — Experiment 7"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2021multitask-exp1/README.md", "public_bytes": 5475976, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2021multitask-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for tomov2021multitask/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-tomov2021multitask-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-tomov2021multitask-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Castle-Room Exploration — Experiment 1"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2021multitask-exp3/README.md", "public_bytes": 5140495, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2021multitask-exp3/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for tomov2021multitask/exp3.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-tomov2021multitask-exp3", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-tomov2021multitask-exp3/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Castle-Room Exploration — Experiment 3"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-waltz2020differential-exp1/README.md", "public_bytes": 1637351, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-waltz2020differential-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for waltz2020differential/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-waltz2020differential-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-waltz2020differential-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Slot-Machine Choices Across Games"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp1/README.md", "public_bytes": 3234483, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp1/README.md", "summary": "Public-data Agent modeling of wilson2014humans/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-wilson2014humans-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wilson2014humans-exp1/README.md", "task_version": "0.1-public-validation", "title": "Human Two-Slot-Machine Choices — Experiment 1"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp2/README.md", "public_bytes": 421444, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp2/README.md", "summary": "Public-data Agent modeling of wilson2014humans/exp2.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-wilson2014humans-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wilson2014humans-exp2/README.md", "task_version": "0.1-public-validation", "title": "Human Two-Slot-Machine Choices — Experiment 2"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp3/README.md", "public_bytes": 4093232, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp3/README.md", "summary": "Public-data Agent modeling of wilson2014humans/exp3.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-wilson2014humans-exp3", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wilson2014humans-exp3/README.md", "task_version": "0.1-public-validation", "title": "Human Two-Slot-Machine Choices — Experiment 3"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp4/README.md", "public_bytes": 4816535, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp4/README.md", "summary": "Public-data Agent modeling of wilson2014humans/exp4.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-wilson2014humans-exp4", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wilson2014humans-exp4/README.md", "task_version": "0.1-public-validation", "title": "Human Two-Slot-Machine Choices — Experiment 4"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp5/README.md", "public_bytes": 2348077, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp5/README.md", "summary": "Public-data Agent modeling of wilson2014humans/exp5.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed.", "task_id": "psych101-wilson2014humans-exp5", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wilson2014humans-exp5/README.md", "task_version": "0.1-public-validation", "title": "Human Two-Slot-Machine Choices — Experiment 5"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wise2019acomputational-exp1/README.md", "public_bytes": 2780468, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wise2019acomputational-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for wise2019acomputational/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-wise2019acomputational-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wise2019acomputational-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Shock-Probability Estimates from Visual Cues"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2018generalisation-exp1/README.md", "public_bytes": 610382, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2018generalisation-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for wu2018generalisation/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-wu2018generalisation-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wu2018generalisation-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Reward Search Along a Number Line"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2023chunking-exp1/README.md", "public_bytes": 10124802, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2023chunking-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for wu2023chunking/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-wu2023chunking-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wu2023chunking-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Responses to Keypress Instructions — Experiment 1"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2023chunking-exp2/README.md", "public_bytes": 8120731, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2023chunking-exp2/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for wu2023chunking/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-wu2023chunking-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wu2023chunking-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Responses to Keypress Instructions — Experiment 2"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wulff2018description-exp1/README.md", "public_bytes": 6404480, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wulff2018description-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for wulff2018description/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-wulff2018description-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wulff2018description-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Choices Between Described Monetary Lotteries"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wulff2018sampling-exp1/README.md", "public_bytes": 46735079, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wulff2018sampling-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for wulff2018sampling/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-wulff2018sampling-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wulff2018sampling-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Lottery Sampling and Final Choice"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-xiong2023neural-exp1/README.md", "public_bytes": 5105998, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-xiong2023neural-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for xiong2023neural/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-xiong2023neural-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-xiong2023neural-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Choices with Changing Slot-Machine Rewards"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zhu2020bayesian-exp1/README.md", "public_bytes": 886928, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zhu2020bayesian-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for zhu2020bayesian/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-zhu2020bayesian-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-zhu2020bayesian-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Weather-Probability Estimates — Experiment 1"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zhu2020bayesian-exp2/README.md", "public_bytes": 1742494, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zhu2020bayesian-exp2/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for zhu2020bayesian/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-zhu2020bayesian-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-zhu2020bayesian-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Conditional Weather-Probability Estimates"} -{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zorowitz2023data-exp1/README.md", "public_bytes": 5483507, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zorowitz2023data-exp1/README.md", "summary": "Public Psych-101 marked-response UTF-8 byte+EOS likelihood for zorowitz2023data/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores.", "task_id": "psych101-zorowitz2023data-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-zorowitz2023data-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Rocket and Alien Choices for Treasure"} +{"access": "hosted_public", "agent_results": "historical_v0_only", "collection": "v1", "data_category": "calcium-imaging", "metric_direction": "See task protocol", "primary_metric": "See task protocol", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/calcium-imaging/neuro-rsc-place-cell/README.md", "public_bytes": 203632523, "public_file_count": 1, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/calcium-imaging/neuro-rsc-place-cell/README.md", "summary": "The agent performs five analyses of RSC place-cell dynamics using the staged recording.", "task_id": "neuro-rsc-place-cell", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/calcium-imaging/neuro-rsc-place-cell/README.md", "task_version": "0.2", "title": "neuro-rsc-place-cell"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "connectomics", "metric_direction": "maximize", "primary_metric": "score", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/connectomics/celegans-structure-function-divergence/README.md", "public_bytes": 1063606, "public_file_count": 3, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/connectomics/celegans-structure-function-divergence/README.md", "summary": "How closely does anatomical wiring match measured signal propagation in C. elegans? The agent quantifies differences between a connectome and a signaling atlas using a fixed analysis protocol. It compares connections, communities, hubs, and pharyngeal organization. The evaluator runs the submitted analyzer on additional reconstructions and compares its outputs with independent calculations. The task measures differences between the networks, not predictions of one network from the other.", "task_id": "celegans-structure-function-divergence", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/connectomics/celegans-structure-function-divergence/README.md", "task_version": "0.6", "title": "Anatomical Connectivity and Signal Propagation in C. elegans"} +{"access": "hosted_public", "agent_results": "historical_v0_only", "collection": "v1", "data_category": "eeg", "metric_direction": "See task protocol", "primary_metric": "See task protocol", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/bciciv-2a/README.md", "public_bytes": 202714474, "public_file_count": 1, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/bciciv-2a/README.md", "summary": "The agent designs a PyTorch nn.Module MIAgentModel that classifies a (B, 22, 512) tensor of cue-relative, 4–38 Hz motor-imagery EEG (128 Hz, microvolts) into 4 classes (left hand / right hand / feet / tongue).", "task_id": "bciciv-2a", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/bciciv-2a/README.md", "task_version": "0.2", "title": "bciciv-2a — 4-class Motor Imagery decoding (BCI Competition IV 2a)"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-cvep-thielen2015/README.md", "public_bytes": 119737938, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-cvep-thielen2015/README.md", "summary": "This task asks an agent to classify one-second cVEP EEG windows into 36 native classes. The source protocol keeps train and validation subjects separate.", "task_id": "eeg-cvep-thielen2015", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-cvep-thielen2015/README.md", "task_version": "0.1-public-validation", "title": "Thielen2015 cVEP decoding"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-dementia-dice/README.md", "public_bytes": 510942124, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-dementia-dice/README.md", "summary": "The DICE research task classifies five-second EEG windows from source-labeled Alzheimer's, dementia, and healthy groups. Train and validation subjects do not overlap. This is a research classification task, not clinical diagnostic validation.", "task_id": "eeg-dementia-dice", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-dementia-dice/README.md", "task_version": "0.1-public-validation", "title": "DICE EEG classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-erp-ern/README.md", "public_bytes": 185087647, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-ern/README.md", "summary": "This ERN task distinguishes one-second EEG windows labeled Target and NonTarget in the source. The validation subjects do not appear in the training split.", "task_id": "eeg-erp-ern", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-erp-ern/README.md", "task_version": "0.1-public-validation", "title": "ERN EEG classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-erp-lrp/README.md", "public_bytes": 185087647, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-lrp/README.md", "summary": "This LRP task classifies one-second EEG windows as source-labeled Target or NonTarget. The native split tests the method on subjects held out from training.", "task_id": "eeg-erp-lrp", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-erp-lrp/README.md", "task_version": "0.1-public-validation", "title": "LRP EEG classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-erp-mmn/README.md", "public_bytes": 460888332, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-mmn/README.md", "summary": "This mismatch-negativity task distinguishes source-labeled Target and NonTarget EEG windows. Each window lasts one second, and train and validation use disjoint subject groups.", "task_id": "eeg-erp-mmn", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-erp-mmn/README.md", "task_version": "0.1-public-validation", "title": "Mismatch-negativity EEG classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-erp-n170/README.md", "public_bytes": 148243682, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n170/README.md", "summary": "This N170 task distinguishes one-second EEG windows labeled Target and NonTarget in the source. Its validation split contains subjects absent from training.", "task_id": "eeg-erp-n170", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-erp-n170/README.md", "task_version": "0.1-public-validation", "title": "N170 EEG classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-erp-n2pc/README.md", "public_bytes": 148345021, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n2pc/README.md", "summary": "This N2pc task classifies one-second EEG windows as source-labeled Target or NonTarget. The task uses a subject-disjoint public validation split.", "task_id": "eeg-erp-n2pc", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-erp-n2pc/README.md", "task_version": "0.1-public-validation", "title": "N2pc EEG classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-erp-n400/README.md", "public_bytes": 55590922, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n400/README.md", "summary": "This N400 task distinguishes one-second EEG windows labeled Target and NonTarget in the source. The source protocol separates training and validation subjects.", "task_id": "eeg-erp-n400", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-erp-n400/README.md", "task_version": "0.1-public-validation", "title": "N400 EEG classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-erp-p3/README.md", "public_bytes": 92652002, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-p3/README.md", "summary": "This P3 task uses one-second EEG windows from the Kappenman2021 source case and two native classes. Its public validation subjects are separate from the training subjects.", "task_id": "eeg-erp-p3", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-erp-p3/README.md", "task_version": "0.1-public-validation", "title": "Kappenman2021 P3 EEG classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-me-highgamma2017/README.md", "public_bytes": 2041458389, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-me-highgamma2017/README.md", "summary": "This task classifies three-second EEG windows from the High-Gamma motor-execution protocol into four native classes. The native split separates subjects between training and validation.", "task_id": "eeg-me-highgamma2017", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-me-highgamma2017/README.md", "task_version": "0.1-public-validation", "title": "High-Gamma motor-execution classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-me-ofner2017/README.md", "public_bytes": 443100882, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-me-ofner2017/README.md", "summary": "This Ofner2017 task asks an agent to classify three-second motor-execution EEG windows into seven native classes. Training and validation use different subjects.", "task_id": "eeg-me-ofner2017", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-me-ofner2017/README.md", "task_version": "0.1-public-validation", "title": "Ofner2017 motor-execution classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-mental-arithmetic-zyma2019/README.md", "public_bytes": 63605750, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mental-arithmetic-zyma2019/README.md", "summary": "This Zyma2019 task classifies five-second mental-arithmetic EEG windows into two native classes. Its public validation split is subject-disjoint.", "task_id": "eeg-mental-arithmetic-zyma2019", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-mental-arithmetic-zyma2019/README.md", "task_version": "0.1-public-validation", "title": "Zyma2019 mental-arithmetic classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-mi-barachant2012/README.md", "public_bytes": 11825808, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-barachant2012/README.md", "summary": "This AlexMI task asks an agent to classify four-second motor-imagery EEG windows into three native classes. The split separates trigger indices and excludes overlapping windows on the same timeline.", "task_id": "eeg-mi-barachant2012", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-mi-barachant2012/README.md", "task_version": "0.1-public-validation", "title": "AlexMI motor-imagery classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-mi-bnci2014/README.md", "public_bytes": 170344916, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-bnci2014/README.md", "summary": "This task classifies four-second BCI-IV-2a EEG windows into four source-defined motor-imagery classes. It retains the native subject grouping from the frozen AgentEEGBench protocol. It is not the legacy bciciv-2a task, which fits session T and scores session E per subject.", "task_id": "eeg-mi-bnci2014", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-mi-bnci2014/README.md", "task_version": "0.1-public-validation", "title": "BCI-IV-2a native motor-imagery classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-mi-cho2017/README.md", "public_bytes": 1023001442, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-cho2017/README.md", "summary": "This Cho2017 task classifies four-second motor-imagery EEG windows into two native classes. The source protocol reserves separate subjects for validation.", "task_id": "eeg-mi-cho2017", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-mi-cho2017/README.md", "task_version": "0.1-public-validation", "title": "Cho2017 motor-imagery classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-mi-eegmmidb/README.md", "public_bytes": 929308208, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-eegmmidb/README.md", "summary": "This EEGMMIDB task uses four-second motor-imagery EEG windows and four native classes. Training and validation subjects do not overlap.", "task_id": "eeg-mi-eegmmidb", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-mi-eegmmidb/README.md", "task_version": "0.1-public-validation", "title": "EEGMMIDB motor-imagery classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-mi-openbmi2019/README.md", "public_bytes": 1024405402, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-openbmi2019/README.md", "summary": "This OpenBMI motor-imagery task asks an agent to classify four-second EEG windows into two native classes. Its native split keeps validation subjects out of training.", "task_id": "eeg-mi-openbmi2019", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-mi-openbmi2019/README.md", "task_version": "0.1-public-validation", "title": "OpenBMI motor-imagery classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-mi-zhou2016/README.md", "public_bytes": 32355620, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-zhou2016/README.md", "summary": "This Zhou2016 task classifies four-second motor-imagery EEG windows into three native classes. The source protocol places training and validation in separate sessions.", "task_id": "eeg-mi-zhou2016", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-mi-zhou2016/README.md", "task_version": "0.1-public-validation", "title": "Zhou2016 motor-imagery classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-p3-openbmi2019/README.md", "public_bytes": 10623665898, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-p3-openbmi2019/README.md", "summary": "This OpenBMI P3 task uses one-second EEG windows and two native classes. Training and validation use disjoint subjects under the source protocol.", "task_id": "eeg-p3-openbmi2019", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-p3-openbmi2019/README.md", "task_version": "0.1-public-validation", "title": "OpenBMI P3 EEG classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-sleep-stage-sleepedf/README.md", "public_bytes": 4453124284, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-sleep-stage-sleepedf/README.md", "summary": "This task classifies 30-second Sleep-EDF cassette EEG windows into N1, N2, N3, R, and W. It uses a full native export from 78 subjects. The native pipeline crops wake time to 30 minutes and uses a subject-disjoint split.", "task_id": "eeg-sleep-stage-sleepedf", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-sleep-stage-sleepedf/README.md", "task_version": "0.1-public-validation", "title": "Sleep-EDF cassette sleep-stage classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-ssvep-openbmi2019/README.md", "public_bytes": 1024405402, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-ssvep-openbmi2019/README.md", "summary": "This OpenBMI SSVEP task asks an agent to classify four-second EEG windows into four native classes. The public validation subjects are separate from training subjects.", "task_id": "eeg-ssvep-openbmi2019", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-ssvep-openbmi2019/README.md", "task_version": "0.1-public-validation", "title": "OpenBMI SSVEP classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-ssvep-wang2017/README.md", "public_bytes": 796760562, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-ssvep-wang2017/README.md", "summary": "This Wang2017 SSVEP task classifies four-second EEG windows into 40 native classes. The native split evaluates the chosen method on different subjects.", "task_id": "eeg-ssvep-wang2017", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-ssvep-wang2017/README.md", "task_version": "0.1-public-validation", "title": "Wang2017 SSVEP classification"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "eeg", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-typing-spanishbcbl/README.md", "public_bytes": 3539526604, "public_file_count": 4, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-typing-spanishbcbl/README.md", "summary": "This task classifies one-second typing-related EEG windows into 29 source-defined output classes. The mapping includes characters, space, a number group, and a special-symbol group. The native SimilaritySplit separates train and validation by sentence-similarity clusters.", "task_id": "eeg-typing-spanishbcbl", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/eeg-typing-spanishbcbl/README.md", "task_version": "0.1-public-validation", "title": "SpanishBCBL EEG typing classification"} +{"access": "hosted_public", "agent_results": "historical_v0_only", "collection": "v1", "data_category": "eeg", "metric_direction": "See task protocol", "primary_metric": "See task protocol", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/sleep-edf/README.md", "public_bytes": 1225526664, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/sleep-edf/README.md", "summary": "The agent designs a PyTorch nn.Module SleepAgentModel that classifies a (B, 1, 3000) tensor of preprocessed Fpz-Cz sleep EEG (30 s epoch at 100 Hz, microvolts) into 5 sleep stages (Wake / N1 / N2 / N3 / REM).", "task_id": "sleep-edf", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/eeg/sleep-edf/README.md", "task_version": "0.2", "title": "sleep-edf — 5-class Sleep Staging (Sleep-EDF Cassette)"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "invasive", "metric_direction": "minimize", "primary_metric": "normalized_spectrogram_MSE", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/intracortical/falcon-b1-birdsong/README.md", "public_bytes": 170230855, "public_file_count": 11, "source_url": "https://dandiarchive.org/dandiset/001046/draft", "summary": "A Neuropixels probe recorded 85 threshold-crossing channels from a singing zebra finch. The task predicts one vocalization spectrogram for each complete song motif. It is not a human speech task.", "task_id": "falcon-b1-birdsong", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/invasive/falcon-b1-birdsong/README.md", "task_version": "0.1-public-validation-motif", "title": "B1: birdsong spectrogram"} +{"access": "source_only", "agent_results": "not_yet_available", "collection": "v1", "data_category": "invasive", "metric_direction": "maximize", "primary_metric": "R2_variance_weighted", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/intracortical/falcon-h1-reach-grasp/README.md", "public_bytes": 0, "public_file_count": 0, "source_url": "https://dandiarchive.org/dandiset/000954/draft", "summary": "A human participant watched a virtual arm and attempted arm and grasp movements. Utah arrays recorded threshold crossings in motor cortex. The task predicts seven commanded velocities, not measured arm movement. Read the FALCON dataset description and the native loader.", "task_id": "falcon-h1-reach-grasp", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/invasive/falcon-h1-reach-grasp/README.md", "task_version": "0.1-public-validation-stream", "title": "H1: attempted reach and grasp"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "invasive", "metric_direction": "minimize", "primary_metric": "WER", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/intracortical/falcon-h2-handwriting/README.md", "public_bytes": 1110017522, "public_file_count": 86, "source_url": "https://dandiarchive.org/dandiset/000950/0.241029.1403", "summary": "A BrainGate2 participant attempted to write prompted English sentences while intracortical arrays recorded spike counts. The task decodes one sentence after each complete trial.", "task_id": "falcon-h2-handwriting", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/invasive/falcon-h2-handwriting/README.md", "task_version": "0.1-public-validation-stream", "title": "H2: attempted handwriting"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "invasive", "metric_direction": "maximize", "primary_metric": "R2_variance_weighted", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/intracortical/falcon-m1-emg/README.md", "public_bytes": 134424422, "public_file_count": 18, "source_url": "https://dandiarchive.org/dandiset/000941/0.241029.1405", "summary": "This task predicts 16 upper-limb muscle signals from 64 intracortical channels during macaque reach and grasp.", "task_id": "falcon-m1-emg", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/invasive/falcon-m1-emg/README.md", "task_version": "0.1-public-validation-stream", "title": "M1-A: upper-limb EMG"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "invasive", "metric_direction": "maximize", "primary_metric": "R2_variance_weighted", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/intracortical/falcon-m2-finger-velocity/README.md", "public_bytes": 13234392, "public_file_count": 30, "source_url": "https://dandiarchive.org/dandiset/000953/draft", "summary": "This task predicts two finger-group velocities from 96 macaque intracortical channels during finger control.", "task_id": "falcon-m2-finger-velocity", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/invasive/falcon-m2-finger-velocity/README.md", "task_version": "0.1-public-validation-stream", "title": "M2: finger-group velocity"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "invasive", "metric_direction": "maximize", "primary_metric": "balanced_accuracy", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/ieeg/ieeg-film-speech-music/README.md", "public_bytes": 922341200, "public_file_count": 257, "source_url": "https://doi.org/10.18112/openneuro.ds003688.v1.0.7", "summary": "This task classifies speech and music intervals in a film from clinical ECoG and sEEG recordings. It tests held-out film blocks within each participant.", "task_id": "ieeg-film-speech-music", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/invasive/ieeg-film-speech-music/README.md", "task_version": "0.2-complete-guarded-windows", "title": "Film speech versus music from clinical iEEG"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "invasive", "metric_direction": "maximize", "primary_metric": "pearson_r", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/ieeg/ieeg-finger-flexion-bciciv4/README.md", "public_bytes": 324773839, "public_file_count": 14, "source_url": "https://www.bbci.de/competition/iv/", "summary": "This task predicts continuous finger flexion from ECoG recordings in three participants. Each model returns five trajectories, while the score uses four fingers.", "task_id": "ieeg-finger-flexion-bciciv4", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/invasive/ieeg-finger-flexion-bciciv4/README.md", "task_version": "0.1-public-validation-offline", "title": "BCI Competition IV Dataset 4: finger flexion"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "mri", "metric_direction": "minimize", "primary_metric": "test_mae", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/mri/brain-age-mri/README.md", "public_bytes": 3729262581, "public_file_count": 1, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/mri/brain-age-mri/README.md", "summary": "The agent develops a model that predicts chronological age from T1-weighted brain MRI. Model development uses public images and age labels. Evaluation uses a separate set of held-out subjects.", "task_id": "brain-age-mri", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/mri/brain-age-mri/README.md", "task_version": "0.1-candidate", "title": "Age Prediction from Structural MRI"} +{"access": "hosted_public", "agent_results": "historical_v0_only", "collection": "v1", "data_category": "mri", "metric_direction": "See task protocol", "primary_metric": "See task protocol", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/mri/tops-fmri/README.md", "public_bytes": 965667246, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/mri/tops-fmri/README.md", "summary": "The agent trains a linear 279 ROI / 38781 edge functional-connectivity signature on the public Study3 fMRI dynamic-FC data (dfc_5bin_dat × CAPS/REST + pain ratings).", "task_id": "tops-fmri", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/mri/tops-fmri/README.md", "task_version": "0.1", "title": "tops-fmri — Tonic Pain Signature (linear FC, external validation)"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-badham2017deficits-exp1/README.md", "public_bytes": 2304677, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-badham2017deficits-exp1/README.md", "summary": "Participants classify geometric objects as E or K across four rule problems and receive feedback. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-badham2017deficits-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-badham2017deficits-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Category Learning from Feedback"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-bahrami2020four-exp/README.md", "public_bytes": 5106777, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-bahrami2020four-exp/README.md", "summary": "Participants repeatedly choose among four labeled options and observe the points earned. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-bahrami2020four-exp", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-bahrami2020four-exp/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Choices Among Four Rewards"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/README.md", "public_bytes": 3027152, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/README.md", "summary": "Participants estimate a target hormone level from two verbally described hormone levels. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-collsioo2023mcpl-exp1-775cd1984f", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Hormone-Level Estimates from Verbal Cues"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/README.md", "public_bytes": 3201056, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/README.md", "summary": "Participants estimate a target hormone level from two numbered hormone levels. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-collsioo2023mcpl-exp2-6bd18ff5bf", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Hormone-Level Estimates from Numeric Cues"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/README.md", "public_bytes": 2025867, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/README.md", "summary": "Participants estimate a target hormone level from two verbally described hormone levels. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-collsioo2023mcpl-exp3-c372064286", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Hormone-Level Estimates from Two Cues"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-cox2017information-exp1/README.md", "public_bytes": 8684274, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-cox2017information-exp1/README.md", "summary": "Participants study word pairs and judge whether a later pair appeared together in the study list. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-cox2017information-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-cox2017information-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Recognition of Studied Word Pairs"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/README.md", "public_bytes": 8466948, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/README.md", "summary": "Participants compare each letter with the one shown N trials earlier and press a match or nonmatch key. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-enkavi2019adaptivenback-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human N-Back Letter Responses"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-enkavi2019digitspan-exp1/README.md", "public_bytes": 5692403, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019digitspan-exp1/README.md", "summary": "Participants view a digit sequence and type the digits in their remembered order. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-enkavi2019digitspan-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-enkavi2019digitspan-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Digit-Sequence Recall"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-enkavi2019gonogo-exp1/README.md", "public_bytes": 7564952, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019gonogo-exp1/README.md", "summary": "Participants press a key for one color and withhold a response for another color. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-enkavi2019gonogo-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-enkavi2019gonogo-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Go/No-Go Keypresses"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-enkavi2019recentprobes-exp1/README.md", "public_bytes": 3678382, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019recentprobes-exp1/README.md", "summary": "Participants remember six letters and judge whether a later probe letter belonged to that list. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-enkavi2019recentprobes-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-enkavi2019recentprobes-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Recognition of Recent Letters"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-feng2021dynamics-exp1/README.md", "public_bytes": 3114689, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-feng2021dynamics-exp1/README.md", "summary": "Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-feng2021dynamics-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-feng2021dynamics-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Choices Between Changing Slot Machines"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-flesch2018comparing-exp1/README.md", "public_bytes": 31867420, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-flesch2018comparing-exp1/README.md", "summary": "Participants accept or reject trees that vary in leaves and branches across two gardens, with feedback during training. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-flesch2018comparing-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-flesch2018comparing-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Tree-Category Learning Across Gardens"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-frey2017cct-exp1/README.md", "public_bytes": 71600868, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-frey2017cct-exp1/README.md", "summary": "Participants turn over gain or loss cards and can stop a round to claim its current payout. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-frey2017cct-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-frey2017cct-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Stop-or-Continue Card Choices"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-frey2017risk-exp1/README.md", "public_bytes": 12928138, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-frey2017risk-exp1/README.md", "summary": "Participants pump a balloon for points or stop to collect the accumulated points. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-frey2017risk-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-frey2017risk-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Balloon Pumping and Stopping"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-garcia2023experiential-exp1/README.md", "public_bytes": 2951357, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp1/README.md", "summary": "Participants choose between reward options across three phases and later estimate each option's chance of winning. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-garcia2023experiential-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-garcia2023experiential-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Reward Choices and Odds Estimates — Experiment 1"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-garcia2023experiential-exp2/README.md", "public_bytes": 2951505, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp2/README.md", "summary": "Participants choose between reward options across three phases and later estimate each option's chance of winning. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-garcia2023experiential-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-garcia2023experiential-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Reward Choices and Odds Estimates — Experiment 2"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-garcia2023experiential-exp3/README.md", "public_bytes": 2917546, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp3/README.md", "summary": "Participants choose between reward options across three phases and later estimate each option's chance of winning. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-garcia2023experiential-exp3", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-garcia2023experiential-exp3/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Reward Choices and Odds Estimates — Experiment 3"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-garcia2023experiential-exp4/README.md", "public_bytes": 2292628, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp4/README.md", "summary": "Participants choose between reward options across three phases and later estimate each option's chance of winning. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-garcia2023experiential-exp4", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-garcia2023experiential-exp4/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Reward Choices and Odds Estimates — Experiment 4"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-gershman2018deconstructing-exp1/README.md", "public_bytes": 319085, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2018deconstructing-exp1/README.md", "summary": "Participants choose between a variable slot machine and one that always gives zero points. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-gershman2018deconstructing-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-gershman2018deconstructing-exp1/README.md", "task_version": "0.1-public-validation", "title": "Human Choices Against a Fixed-Zero Slot Machine"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-gershman2018deconstructing-exp2/README.md", "public_bytes": 321792, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2018deconstructing-exp2/README.md", "summary": "Participants repeatedly choose between two variable slot machines, one of which is better on average. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-gershman2018deconstructing-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-gershman2018deconstructing-exp2/README.md", "task_version": "0.1-public-validation", "title": "Human Choices Between Unequal Slot Machines"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-gershman2020reward-exp1/README.md", "public_bytes": 2322153, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2020reward-exp1/README.md", "summary": "Participants learn which of three keys earns a reward for each presented stimulus. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-gershman2020reward-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-gershman2020reward-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Stimulus–Response Learning from Rewards"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-hebart2023things-exp1/README.md", "public_bytes": 156881709, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-hebart2023things-exp1/README.md", "summary": "Participants select the least similar object from each three-object group. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-hebart2023things-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-hebart2023things-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Odd-One-Out Judgments"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-hilbig2014generalized-exp1/README.md", "public_bytes": 591437, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-hilbig2014generalized-exp1/README.md", "summary": "Participants compare two fictional products using four expert ratings and choose one product. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-hilbig2014generalized-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-hilbig2014generalized-exp1/README.md", "task_version": "0.1-public-validation", "title": "Human Product Choices from Expert Ratings"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-jansen2021dunningkruger-exp1/README.md", "public_bytes": 31736579, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-jansen2021dunningkruger-exp1/README.md", "summary": "Participants estimate how many questions they will answer correctly on a 20-question grammar quiz. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-jansen2021dunningkruger-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-jansen2021dunningkruger-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Grammar Quiz Self-Estimates"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-kool2016when-exp1/README.md", "public_bytes": 2813931, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2016when-exp1/README.md", "summary": "Participants choose spaceships to collect treasure while avoiding antimatter from changing alien mines. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-kool2016when-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-kool2016when-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Spaceship Choices amid Treasure and Antimatter"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-kool2016when-exp2/README.md", "public_bytes": 4096825, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2016when-exp2/README.md", "summary": "Participants choose spaceships and alien mines to collect treasure as mine rewards change. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-kool2016when-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-kool2016when-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Spaceship and Alien Choices for Treasure"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-kool2017cost-exp1/README.md", "public_bytes": 3703289, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2017cost-exp1/README.md", "summary": "Participants choose spaceships for changing treasure rewards after learning whether a reward multiplier applies. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-kool2017cost-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-kool2017cost-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Spaceship Choices with Treasure Multipliers"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-kool2017cost-exp2/README.md", "public_bytes": 3618680, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2017cost-exp2/README.md", "summary": "Participants choose spaceships and alien mines for treasure after learning whether a reward multiplier applies. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-kool2017cost-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-kool2017cost-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Spaceship and Alien Choices with Multipliers"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-krueger2022identifying-exp1/README.md", "public_bytes": 28635461, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-krueger2022identifying-exp1/README.md", "summary": "Participants choose one of six gambles, then receive a payoff linked to the chosen gamble and a drawn ball color. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-krueger2022identifying-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-krueger2022identifying-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Choices Among Six Gambles"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-kumar2023disentangling-exp1/README.md", "public_bytes": 42562418, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kumar2023disentangling-exp1/README.md", "summary": "Participants select unrevealed locations on a 7×7 grid and try to reveal ones while avoiding zeros. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-kumar2023disentangling-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-kumar2023disentangling-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Choices on a Hidden Binary Grid"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md", "public_bytes": 450595, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md", "summary": "Participants visit four casinos and choose between two slot machines to collect stochastic rewards. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-lefebvre2017behavioural-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Choice in a Casino Task"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-lefebvre2017behavioural-exp2/README.md", "public_bytes": 339457, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-lefebvre2017behavioural-exp2/README.md", "summary": "Participants visit four casinos and choose between two machines that can return positive or negative points. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-lefebvre2017behavioural-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-lefebvre2017behavioural-exp2/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Casino Choices with Gains and Losses"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-levering2020revisiting-exp1/README.md", "public_bytes": 1229159, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-levering2020revisiting-exp1/README.md", "summary": "Participants classify objects by shape, size, and shading, then rate category typicality in a test block. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-levering2020revisiting-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-levering2020revisiting-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Object Classification and Typicality Ratings — Experiment 1"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-levering2020revisiting-exp2/README.md", "public_bytes": 995024, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-levering2020revisiting-exp2/README.md", "summary": "Participants classify objects by shape, size, and shading, then rate category typicality in a test block. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-levering2020revisiting-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-levering2020revisiting-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Object Classification and Typicality Ratings — Experiment 2"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-ludwig2023human-exp0/README.md", "public_bytes": 2623321, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp0/README.md", "summary": "Participants move through a fruit market, collect fruits with two vitamins, and feed animals with different preferences. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-ludwig2023human-exp0", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-ludwig2023human-exp0/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Fruit-Market Navigation and Feeding — Experiment 0"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-ludwig2023human-exp1/README.md", "public_bytes": 847355, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp1/README.md", "summary": "Participants move through a fruit market, collect fruits with two vitamins, and feed animals with different preferences. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-ludwig2023human-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-ludwig2023human-exp1/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Fruit-Market Navigation and Feeding — Experiment 1"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-ludwig2023human-exp2/README.md", "public_bytes": 799996, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp2/README.md", "summary": "Participants move through a fruit market, collect fruits with two vitamins, and feed animals with different preferences. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-ludwig2023human-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-ludwig2023human-exp2/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Fruit-Market Navigation and Feeding — Experiment 2"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-peterson2021using-exp1/README.md", "public_bytes": 185996551, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-peterson2021using-exp1/README.md", "summary": "Participants choose between two gambles while some problems show obtained and missed outcomes and others suppress that feedback. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-peterson2021using-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-peterson2021using-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Gamble Choices under Varying Feedback"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-plonsky2018when-exp1/README.md", "public_bytes": 14186060, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-plonsky2018when-exp1/README.md", "summary": "Participants choose between two gambles over repeated encounters, first without feedback and then with both outcomes shown. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-plonsky2018when-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-plonsky2018when-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Gamble Choices before and after Feedback"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-popov2023intent-exp1/README.md", "public_bytes": 897131, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp1/README.md", "summary": "Participants judge word meanings, solve arithmetic problems, and later recall marked words from study lists. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-popov2023intent-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-popov2023intent-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Word Study and Recall — Experiment 1"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-popov2023intent-exp2/README.md", "public_bytes": 722615, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp2/README.md", "summary": "Participants judge paired word meanings, solve arithmetic problems, and later recall marked word pairs. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-popov2023intent-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-popov2023intent-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Word-Pair Study and Recall"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-popov2023intent-exp3/README.md", "public_bytes": 1081021, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp3/README.md", "summary": "Participants judge word meanings, solve arithmetic problems, and later recall marked words from study lists. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-popov2023intent-exp3", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-popov2023intent-exp3/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Word Study and Recall — Experiment 3"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-ruggeri2022globalizability-exp1/README.md", "public_bytes": 20495426, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ruggeri2022globalizability-exp1/README.md", "summary": "Participants state preferences between a payment now and a larger payment after a delay. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-ruggeri2022globalizability-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-ruggeri2022globalizability-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Preferences for Immediate and Delayed Payments"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/README.md", "public_bytes": 2735477, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/README.md", "summary": "Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-sadeghiyeh2020temporal-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Slot-Machine Choices Across Games"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-schulz2020finding-exp1/README.md", "public_bytes": 1693724, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp1/README.md", "summary": "Participants choose among eight reward options over repeated rounds and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-schulz2020finding-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-schulz2020finding-exp1/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Search Among Eight Reward Options — Experiment 1"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-schulz2020finding-exp2/README.md", "public_bytes": 1108447, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp2/README.md", "summary": "Participants choose among eight reward options over repeated rounds and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-schulz2020finding-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-schulz2020finding-exp2/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Search Among Eight Reward Options — Experiment 2"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-schulz2020finding-exp3/README.md", "public_bytes": 1723768, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp3/README.md", "summary": "Participants choose among eight reward options over repeated rounds and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-schulz2020finding-exp3", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-schulz2020finding-exp3/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Search Among Eight Reward Options — Experiment 3"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-schulz2020finding-exp4/README.md", "public_bytes": 1524152, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp4/README.md", "summary": "Participants choose among eight reward options over repeated rounds and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-schulz2020finding-exp4", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-schulz2020finding-exp4/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Search Among Eight Reward Options — Experiment 4"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-schulz2020finding-exp5/README.md", "public_bytes": 2300511, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp5/README.md", "summary": "Participants choose among eight reward options over repeated rounds and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-schulz2020finding-exp5", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-schulz2020finding-exp5/README.md", "task_version": "0.1-public-validation", "title": "Modeling Human Search Among Eight Reward Options — Experiment 5"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-somerville2017charting-exp1/README.md", "public_bytes": 4696596, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-somerville2017charting-exp1/README.md", "summary": "Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-somerville2017charting-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-somerville2017charting-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Exploration of Two Slot Machines"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-speekenbrink2008learning-exp1/README.md", "public_bytes": 497343, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-speekenbrink2008learning-exp1/README.md", "summary": "Participants judge whether combinations of one to three tarot cards predict rainy or fine weather. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-speekenbrink2008learning-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-speekenbrink2008learning-exp1/README.md", "task_version": "0.1-public-validation", "title": "Predicting Human Weather Judgments from Tarot Cards"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-steingroever2015data-exp1/README.md", "public_bytes": 2193605, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp1/README.md", "summary": "Participants draw cards from four decks and experience varying gains and occasional losses. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-steingroever2015data-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-steingroever2015data-exp1/README.md", "task_version": "0.1-public-validation", "title": "Human Choices from Four Card Decks — Experiment 1"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-steingroever2015data-exp2/README.md", "public_bytes": 66396, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp2/README.md", "summary": "Participants draw cards from four decks and experience varying gains and occasional losses. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-steingroever2015data-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-steingroever2015data-exp2/README.md", "task_version": "0.1-public-validation", "title": "Human Choices from Four Card Decks — Experiment 2"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-steingroever2015data-exp3/README.md", "public_bytes": 681645, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp3/README.md", "summary": "Participants draw cards from four decks and experience varying gains and occasional losses. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-steingroever2015data-exp3", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-steingroever2015data-exp3/README.md", "task_version": "0.1-public-validation", "title": "Human Choices from Four Card Decks — Experiment 3"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-tomov2020discovery-exp2/README.md", "public_bytes": 12159394, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp2/README.md", "summary": "Participants plan routes from a start station to a goal through an unfamiliar subway network. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-tomov2020discovery-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-tomov2020discovery-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Subway Navigation — Experiment 2"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-tomov2020discovery-exp4/README.md", "public_bytes": 3021550, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp4/README.md", "summary": "Participants plan routes from a start station to a goal through an unfamiliar subway network. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-tomov2020discovery-exp4", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-tomov2020discovery-exp4/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Subway Navigation — Experiment 4"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-tomov2020discovery-exp5/README.md", "public_bytes": 12369221, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp5/README.md", "summary": "Participants plan routes from a start station to a goal through an unfamiliar subway network. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-tomov2020discovery-exp5", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-tomov2020discovery-exp5/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Subway Navigation — Experiment 5"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-tomov2020discovery-exp7/README.md", "public_bytes": 8601475, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp7/README.md", "summary": "Participants plan routes from a start station to a goal through an unfamiliar subway network. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-tomov2020discovery-exp7", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-tomov2020discovery-exp7/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Subway Navigation — Experiment 7"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-tomov2021multitask-exp1/README.md", "public_bytes": 5475976, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2021multitask-exp1/README.md", "summary": "Participants choose doors between castle rooms to find wood, stone, and iron resources. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-tomov2021multitask-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-tomov2021multitask-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Castle-Room Exploration — Experiment 1"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-tomov2021multitask-exp3/README.md", "public_bytes": 5140495, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2021multitask-exp3/README.md", "summary": "Participants choose doors between castle rooms to find wood, stone, and iron resources. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-tomov2021multitask-exp3", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-tomov2021multitask-exp3/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Castle-Room Exploration — Experiment 3"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-waltz2020differential-exp1/README.md", "public_bytes": 1637351, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-waltz2020differential-exp1/README.md", "summary": "Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-waltz2020differential-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-waltz2020differential-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Slot-Machine Choices Across Games"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wilson2014humans-exp1/README.md", "public_bytes": 3234483, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp1/README.md", "summary": "Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-wilson2014humans-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wilson2014humans-exp1/README.md", "task_version": "0.1-public-validation", "title": "Human Two-Slot-Machine Choices — Experiment 1"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wilson2014humans-exp2/README.md", "public_bytes": 421444, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp2/README.md", "summary": "Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-wilson2014humans-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wilson2014humans-exp2/README.md", "task_version": "0.1-public-validation", "title": "Human Two-Slot-Machine Choices — Experiment 2"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wilson2014humans-exp3/README.md", "public_bytes": 4093232, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp3/README.md", "summary": "Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-wilson2014humans-exp3", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wilson2014humans-exp3/README.md", "task_version": "0.1-public-validation", "title": "Human Two-Slot-Machine Choices — Experiment 3"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wilson2014humans-exp4/README.md", "public_bytes": 4816535, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp4/README.md", "summary": "Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-wilson2014humans-exp4", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wilson2014humans-exp4/README.md", "task_version": "0.1-public-validation", "title": "Human Two-Slot-Machine Choices — Experiment 4"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wilson2014humans-exp5/README.md", "public_bytes": 2348077, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp5/README.md", "summary": "Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-wilson2014humans-exp5", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wilson2014humans-exp5/README.md", "task_version": "0.1-public-validation", "title": "Human Two-Slot-Machine Choices — Experiment 5"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wise2019acomputational-exp1/README.md", "public_bytes": 2780468, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wise2019acomputational-exp1/README.md", "summary": "Participants rate the probability of a shock for visual stimuli and then see each outcome. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-wise2019acomputational-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wise2019acomputational-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Shock-Probability Estimates from Visual Cues"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wu2018generalisation-exp1/README.md", "public_bytes": 610382, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2018generalisation-exp1/README.md", "summary": "Participants select numbered options across multiple environments and observe their point rewards. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-wu2018generalisation-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wu2018generalisation-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Reward Search Along a Number Line"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wu2023chunking-exp1/README.md", "public_bytes": 10124802, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2023chunking-exp1/README.md", "summary": "Participants press the instructed key as quickly and accurately as possible. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-wu2023chunking-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wu2023chunking-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Responses to Keypress Instructions — Experiment 1"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wu2023chunking-exp2/README.md", "public_bytes": 8120731, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2023chunking-exp2/README.md", "summary": "Participants press the instructed key as quickly and accurately as possible. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-wu2023chunking-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wu2023chunking-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Responses to Keypress Instructions — Experiment 2"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wulff2018description-exp1/README.md", "public_bytes": 6404480, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wulff2018description-exp1/README.md", "summary": "Participants choose between two lotteries with described outcomes and probabilities. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-wulff2018description-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wulff2018description-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Choices Between Described Monetary Lotteries"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wulff2018sampling-exp1/README.md", "public_bytes": 46735079, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wulff2018sampling-exp1/README.md", "summary": "Participants sample two lotteries to learn their outcomes and probabilities before making rewarded choices. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-wulff2018sampling-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-wulff2018sampling-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Lottery Sampling and Final Choice"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-xiong2023neural-exp1/README.md", "public_bytes": 5105998, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-xiong2023neural-exp1/README.md", "summary": "Participants choose between two slot machines as their expected point rewards change across trials. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-xiong2023neural-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-xiong2023neural-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Human Choices with Changing Slot-Machine Rewards"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-zhu2020bayesian-exp1/README.md", "public_bytes": 886928, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zhu2020bayesian-exp1/README.md", "summary": "Participants type estimates for weather-related event probabilities. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-zhu2020bayesian-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-zhu2020bayesian-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Weather-Probability Estimates — Experiment 1"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-zhu2020bayesian-exp2/README.md", "public_bytes": 1742494, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zhu2020bayesian-exp2/README.md", "summary": "Participants type estimates for conditional probabilities of weather-related events. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-zhu2020bayesian-exp2", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-zhu2020bayesian-exp2/README.md", "task_version": "0.2-byte-next-v1", "title": "Modeling Human Conditional Weather-Probability Estimates"} +{"access": "hosted_public", "agent_results": "not_yet_available", "collection": "v1", "data_category": "psychology", "metric_direction": "minimize", "primary_metric": "mean_response_nll", "protocol_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-zorowitz2023data-exp1/README.md", "public_bytes": 5483507, "public_file_count": 2, "source_url": "https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zorowitz2023data-exp1/README.md", "summary": "Participants choose rockets to reach planets, then choose aliens to trade with for treasure. The agent predicts participants' recorded responses from the information available before each response.", "task_id": "psych101-zorowitz2023data-exp1", "task_url": "https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/blob/main/tasks/psychology/psych101-zorowitz2023data-exp1/README.md", "task_version": "0.2-byte-next-v1", "title": "Predicting Human Rocket and Alien Choices for Treasure"} diff --git a/tasks/calcium-imaging/neuro-rsc-place-cell/README.md b/tasks/calcium-imaging/neuro-rsc-place-cell/README.md index 174f8fcf1e330c4b6577220aed69496ec5913706..a33931f71543362dc58426e6c62cfc688085d9bf 100644 --- a/tasks/calcium-imaging/neuro-rsc-place-cell/README.md +++ b/tasks/calcium-imaging/neuro-rsc-place-cell/README.md @@ -1,32 +1,26 @@ # neuro-rsc-place-cell -[Task catalog](../../../README.md) +The agent performs five analyses of RSC place-cell dynamics using the staged recording. -RSC 位置细胞动态分析——依据 mouse RSC Ca²⁺ imaging + VR belt 行为数据(VRBeltReframe.mat),完成位置细胞筛选/可视化/贝叶斯解码/trial-bin 相关/firing-rate 动态,交 benchmark_summary.json + report.md + 图。 +Historical Agent results for this retained task are recorded in the v0 report. -Historical results for this retained task remain in the v0 report. +## Task at a glance -## Task and data - -| Field | Value | +| Field | Task contract | |---|---| -| Task ID | `neuro-rsc-place-cell` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2` | -| Data category | Calcium imaging | -| Access | `hosted_public` | -| Primary metric | `See task protocol` (See task protocol) | - -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/calcium-imaging/neuro-rsc-place-cell/public) contains 1 files (203,632,523 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. - -## Protocol and source +| Input | Mouse retrosplenial cortex Ca²⁺ imaging and virtual-reality belt behavior. | +| Output | `benchmark_summary.json`, `report.md`, and `figures/*.png`. | +| Evaluation | A deterministic check compares the summary with a frozen reference. Human review scores the report and figures separately. | +| Metric | Equal-weight mean of `place_cell_ratio_ok`, `decoding_significance_ok`, and `decoding_error_within_tolerance`. Human dimensions do not enter this score. | -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/calcium-imaging/neuro-rsc-place-cell/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Data access -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/calcium-imaging/neuro-rsc-place-cell/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/calcium-imaging/neuro-rsc-place-cell/public) contains 1 file (203,632,523 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. Original source terms apply. This catalog does not relicense the data. + +## Protocol and source + +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/calcium-imaging/neuro-rsc-place-cell/README.md) defines the scientific protocol, preparation, and scoring. + +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/calcium-imaging/neuro-rsc-place-cell/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/connectomics/celegans-structure-function-divergence/README.md b/tasks/connectomics/celegans-structure-function-divergence/README.md index c654cee074564b15176db0fa0e0274c415b16fb9..cd34bcc3c0fdee417ebf8c6c2c071574afddc1e9 100644 --- a/tasks/connectomics/celegans-structure-function-divergence/README.md +++ b/tasks/connectomics/celegans-structure-function-divergence/README.md @@ -1,32 +1,30 @@ # Anatomical Connectivity and Signal Propagation in C. elegans -[Task catalog](../../../README.md) +How closely does anatomical wiring match measured signal propagation in C. elegans? The agent quantifies differences between a connectome and a signaling atlas using a fixed analysis protocol. It compares connections, communities, hubs, and pharyngeal organization. -Candidate integration of an analysis task comparing a measured C. elegans signaling atlas with electron-microscopy connectomes. The agent implements a reusable pipeline for edge ranking, binary-topology community alignment, hub agreement, and pharyngeal co-assignment. A separately isolated evaluator checks numerical outputs on held-out reconstructions; only the public reconstruction and task instructions are available during development. +The evaluator runs the submitted analyzer on additional reconstructions and compares its outputs with independent calculations. The task measures differences between the networks, not predictions of one network from the other. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +Agent benchmark results are not yet available. -## Task and data +## Task at a glance -| Field | Value | +| Field | Details | |---|---| | Task ID | `celegans-structure-function-divergence` | -| Collection | BrainPilotBench v1 | | Task version | `0.6` | -| Data category | Connectomics | -| Access | `hosted_public` | -| Primary metric | `score` (maximize) | +| Public data | A signal propagation atlas, one anatomical connectome reconstruction, and neuron metadata | +| Submission | A reusable Python analyzer, a protocol declaration, and a scientific report | +| Primary metric | `score` in [0, 1]: numerical-statistic agreement weighted by judgment skill, higher is better | +| Evaluation | Statistics and judgments checked on evaluator-controlled reconstructions | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/connectomics/celegans-structure-function-divergence/public) contains 3 files (1,063,606 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/connectomics/celegans-structure-function-divergence/public) contains 3 files (1,063,606 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/connectomics/celegans-structure-function-divergence/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +Original source terms apply. This catalog does not relicense the data. -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/connectomics/celegans-structure-function-divergence/README.md) · [Source attribution](../../../ATTRIBUTION.md) +## Protocol and source -Original source terms apply. This catalog does not relicense the data. +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/connectomics/celegans-structure-function-divergence/README.md) defines the scientific protocol, preparation, and scoring. + +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/connectomics/celegans-structure-function-divergence/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/bciciv-2a/README.md b/tasks/eeg/bciciv-2a/README.md index 885b8cf65342a46d6fe65105d24be9744963a941..363fd56f6fe0f5d1cd09716545268239cdfca54f 100644 --- a/tasks/eeg/bciciv-2a/README.md +++ b/tasks/eeg/bciciv-2a/README.md @@ -1,32 +1,26 @@ # bciciv-2a — 4-class Motor Imagery decoding (BCI Competition IV 2a) -[Task catalog](../../../README.md) +The agent designs a PyTorch `nn.Module` **MIAgentModel** that classifies a `(B, 22, 512)` tensor of cue-relative, 4–38 Hz motor-imagery EEG (128 Hz, microvolts) into 4 classes (left hand / right hand / feet / tongue). -4-class motor-imagery decoding on BCI Competition IV Dataset 2a (9 subjects, within-subject cross-session: session T for training, session E for blind test). The agent submits a single PyTorch `MIAgentModel` class (no direct reuse of braindecode's prebuilt decoders); the scorer trains and infers per subject, reporting per-subject accuracy and Cohen's kappa with mean_kappa as the primary metric. +Historical Agent results for this retained task are recorded in the v0 report. -Historical results for this retained task remain in the v0 report. +## Task at a glance -## Task and data - -| Field | Value | +| Field | Task contract | |---|---| -| Task ID | `bciciv-2a` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `See task protocol` (See task protocol) | - -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/bciciv-2a/public) contains 1 files (202,714,474 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. - -## Protocol and source +| Input | Cue-relative, 4–38 Hz motor-imagery EEG: `(B, 22, 512)` at 128 Hz. | +| Output | Four-class `MIAgentModel` prediction: left hand, right hand, feet, or tongue. | +| Split | Session T has a 230/58 stratified train/valid split per subject. Private session E has 288 trials per subject. | +| Metric | Mean Cohen’s kappa across nine subjects; the leaderboard `score` clips `mean_kappa` to `[0,1]`. | -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/bciciv-2a/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Data access -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/bciciv-2a/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/bciciv-2a/public) contains 1 file (202,714,474 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. Original source terms apply. This catalog does not relicense the data. + +## Protocol and source + +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/bciciv-2a/README.md) defines the scientific protocol, preparation, and scoring. + +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/bciciv-2a/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-cvep-thielen2015/README.md b/tasks/eeg/eeg-cvep-thielen2015/README.md index 37dd9c7fb07db98a35a006b651ceb1eefe36a3ec..0a2a16e3de00e7fdc5bcfd0def06055d1839be68 100644 --- a/tasks/eeg/eeg-cvep-thielen2015/README.md +++ b/tasks/eeg/eeg-cvep-thielen2015/README.md @@ -1,32 +1,29 @@ # Thielen2015 cVEP decoding -[Task catalog](../../../README.md) +This task asks an agent to classify one-second cVEP EEG windows into 36 native classes. The source protocol keeps train and validation subjects separate. -Thielen2015 cVEP; frozen cvep/thielen2015 protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-cvep-thielen2015` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `cvep/thielen2015` (`thielen2015`) | +| EEG input | 64 channels · 120 Hz · 1 s · `[64, 120]` samples | +| Public windows | 2,592 train · 1,296 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 36 native classes · normalized probabilities `[B, 36]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-cvep-thielen2015/public) contains 4 files (119,737,938 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-cvep-thielen2015/public) contains 4 files (119,737,938 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-cvep-thielen2015/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-cvep-thielen2015/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-cvep-thielen2015/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-cvep-thielen2015/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-dementia-dice/README.md b/tasks/eeg/eeg-dementia-dice/README.md index bfeb7eab72d313e71880f16773c5e6ff13abf4b1..04946034953ac761fceb33316d7c810f2d6b92ee 100644 --- a/tasks/eeg/eeg-dementia-dice/README.md +++ b/tasks/eeg/eeg-dementia-dice/README.md @@ -1,32 +1,29 @@ # DICE EEG classification -[Task catalog](../../../README.md) +The DICE research task classifies five-second EEG windows from source-labeled Alzheimer's, dementia, and healthy groups. Train and validation subjects do not overlap. This is a research classification task, not clinical diagnostic validation. -DICE dementia diagnosis; frozen dementia_diagnosis/default protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-dementia-dice` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `dementia_diagnosis/default` (`Miltiadous2023Dice`) | +| EEG input | 19 channels · 120 Hz · 5 s · `[19, 600]` samples | +| Public windows | 8,323 train · 2,863 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 3 native classes · normalized probabilities `[B, 3]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-dementia-dice/public) contains 4 files (510,942,124 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-dementia-dice/public) contains 4 files (510,942,124 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-dementia-dice/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-dementia-dice/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-dementia-dice/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-dementia-dice/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-erp-ern/README.md b/tasks/eeg/eeg-erp-ern/README.md index 86aad7738bce2f786288c5e3ecc1418c78677739..5f7eea48b203bd275b469fa3dbcc31838d6c3bbc 100644 --- a/tasks/eeg/eeg-erp-ern/README.md +++ b/tasks/eeg/eeg-erp-ern/README.md @@ -1,32 +1,29 @@ # ERN EEG classification -[Task catalog](../../../README.md) +This ERN task distinguishes one-second EEG windows labeled `Target` and `NonTarget` in the source. The validation subjects do not appear in the training split. -ERP CORE ERN; frozen ern/default protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-erp-ern` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `ern/default` (`ERP_CORE`) | +| EEG input | 30 channels · 120 Hz · 1 s · `[30, 120]` samples | +| Public windows | 9,591 train · 3,194 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 2 native classes · normalized probabilities `[B, 2]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-erp-ern/public) contains 4 files (185,087,647 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-erp-ern/public) contains 4 files (185,087,647 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-ern/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-ern/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-erp-ern/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-ern/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-erp-lrp/README.md b/tasks/eeg/eeg-erp-lrp/README.md index d4c385f35445b74942061ad4dc7a449277565554..636c688633a965ce40b995cbcf336a4fa1dbb143 100644 --- a/tasks/eeg/eeg-erp-lrp/README.md +++ b/tasks/eeg/eeg-erp-lrp/README.md @@ -1,32 +1,29 @@ # LRP EEG classification -[Task catalog](../../../README.md) +This LRP task classifies one-second EEG windows as source-labeled `Target` or `NonTarget`. The native split tests the method on subjects held out from training. -ERP CORE LRP; frozen lrp/default protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-erp-lrp` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `lrp/default` (`ERP_CORE`) | +| EEG input | 30 channels · 120 Hz · 1 s · `[30, 120]` samples | +| Public windows | 9,591 train · 3,194 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 2 native classes · normalized probabilities `[B, 2]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-erp-lrp/public) contains 4 files (185,087,647 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-erp-lrp/public) contains 4 files (185,087,647 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-lrp/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-lrp/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-erp-lrp/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-lrp/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-erp-mmn/README.md b/tasks/eeg/eeg-erp-mmn/README.md index 9e97fe3b9861e7b786196072b0e057304e454156..31b1122cda25bbb2d5d08e5b40f3fe20edcab33c 100644 --- a/tasks/eeg/eeg-erp-mmn/README.md +++ b/tasks/eeg/eeg-erp-mmn/README.md @@ -1,32 +1,29 @@ # Mismatch-negativity EEG classification -[Task catalog](../../../README.md) +This mismatch-negativity task distinguishes source-labeled `Target` and `NonTarget` EEG windows. Each window lasts one second, and train and validation use disjoint subject groups. -ERP CORE MMN; frozen mismatch_negativity/default protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-erp-mmn` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `mismatch_negativity/default` (`ERP_CORE`) | +| EEG input | 30 channels · 120 Hz · 1 s · `[30, 120]` samples | +| Public windows | 23,835 train · 8,000 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 2 native classes · normalized probabilities `[B, 2]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-erp-mmn/public) contains 4 files (460,888,332 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-erp-mmn/public) contains 4 files (460,888,332 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-mmn/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-mmn/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-erp-mmn/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-mmn/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-erp-n170/README.md b/tasks/eeg/eeg-erp-n170/README.md index cc39584352b9b39a6133ae73666e859ea5283c1b..a1a2caf2f94bab18e61ab842493d8db916d9f9dd 100644 --- a/tasks/eeg/eeg-erp-n170/README.md +++ b/tasks/eeg/eeg-erp-n170/README.md @@ -1,32 +1,29 @@ # N170 EEG classification -[Task catalog](../../../README.md) +This N170 task distinguishes one-second EEG windows labeled `Target` and `NonTarget` in the source. Its validation split contains subjects absent from training. -ERP CORE N170; frozen n170/default protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-erp-n170` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `n170/default` (`ERP_CORE`) | +| EEG input | 30 channels · 120 Hz · 1 s · `[30, 120]` samples | +| Public windows | 7,680 train · 2,560 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 2 native classes · normalized probabilities `[B, 2]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-erp-n170/public) contains 4 files (148,243,682 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-erp-n170/public) contains 4 files (148,243,682 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n170/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n170/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-erp-n170/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n170/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-erp-n2pc/README.md b/tasks/eeg/eeg-erp-n2pc/README.md index a1d2c058395da3d2640a55541b23e95d916c51ac..39c7ba4c0a708986bffce2935ab077690cbc6052 100644 --- a/tasks/eeg/eeg-erp-n2pc/README.md +++ b/tasks/eeg/eeg-erp-n2pc/README.md @@ -1,32 +1,29 @@ # N2pc EEG classification -[Task catalog](../../../README.md) +This N2pc task classifies one-second EEG windows as source-labeled `Target` or `NonTarget`. The task uses a subject-disjoint public validation split. -ERP CORE N2pc; frozen n2pc/default protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-erp-n2pc` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `n2pc/default` (`ERP_CORE`) | +| EEG input | 30 channels · 120 Hz · 1 s · `[30, 120]` samples | +| Public windows | 7,677 train · 2,570 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 2 native classes · normalized probabilities `[B, 2]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-erp-n2pc/public) contains 4 files (148,345,021 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-erp-n2pc/public) contains 4 files (148,345,021 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n2pc/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n2pc/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-erp-n2pc/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n2pc/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-erp-n400/README.md b/tasks/eeg/eeg-erp-n400/README.md index e46a1d4fdb3794e7c77d2fb42d97bbbe6284517c..a4fcb0e4825fb358e13c6cdc0d15c81f8767eb26 100644 --- a/tasks/eeg/eeg-erp-n400/README.md +++ b/tasks/eeg/eeg-erp-n400/README.md @@ -1,32 +1,29 @@ # N400 EEG classification -[Task catalog](../../../README.md) +This N400 task distinguishes one-second EEG windows labeled `Target` and `NonTarget` in the source. The source protocol separates training and validation subjects. -ERP CORE N400; frozen n400/default protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-erp-n400` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `n400/default` (`ERP_CORE`) | +| EEG input | 30 channels · 120 Hz · 1 s · `[30, 120]` samples | +| Public windows | 2,880 train · 960 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 2 native classes · normalized probabilities `[B, 2]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-erp-n400/public) contains 4 files (55,590,922 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-erp-n400/public) contains 4 files (55,590,922 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n400/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n400/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-erp-n400/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-n400/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-erp-p3/README.md b/tasks/eeg/eeg-erp-p3/README.md index a26134dc7907c755d0f65a3537207558df548cf6..34cc6ff39d4f2103bb9234c661d551ed949f0010 100644 --- a/tasks/eeg/eeg-erp-p3/README.md +++ b/tasks/eeg/eeg-erp-p3/README.md @@ -1,32 +1,29 @@ # Kappenman2021 P3 EEG classification -[Task catalog](../../../README.md) +This P3 task uses one-second EEG windows from the Kappenman2021 source case and two native classes. Its public validation subjects are separate from the training subjects. -ERP CORE P3; frozen p3/kappenman2021p3 protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-erp-p3` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `p3/kappenman2021p3` (`ERP_CORE`) | +| EEG input | 30 channels · 120 Hz · 1 s · `[30, 120]` samples | +| Public windows | 4,800 train · 1,600 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 2 native classes · normalized probabilities `[B, 2]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-erp-p3/public) contains 4 files (92,652,002 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-erp-p3/public) contains 4 files (92,652,002 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-p3/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-p3/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-erp-p3/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-erp-p3/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-me-highgamma2017/README.md b/tasks/eeg/eeg-me-highgamma2017/README.md index 7324fb2d8daa66ad270c2a85202d93a3d15b0826..37fac0d5cadda738508abc1b7c633a941a468633 100644 --- a/tasks/eeg/eeg-me-highgamma2017/README.md +++ b/tasks/eeg/eeg-me-highgamma2017/README.md @@ -1,32 +1,29 @@ # High-Gamma motor-execution classification -[Task catalog](../../../README.md) +This task classifies three-second EEG windows from the High-Gamma motor-execution protocol into four native classes. The native split separates subjects between training and validation. -High-Gamma motor execution; frozen motor_execution/schirrmeister2017 protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-me-highgamma2017` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `motor_execution/schirrmeister2017` (`highgamma-schirrmeister2017`) | +| EEG input | 128 channels · 120 Hz · 3 s · `[128, 360]` samples | +| Public windows | 8,111 train · 2,960 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 4 native classes · normalized probabilities `[B, 4]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-me-highgamma2017/public) contains 4 files (2,041,458,389 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-me-highgamma2017/public) contains 4 files (2,041,458,389 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-me-highgamma2017/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-me-highgamma2017/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-me-highgamma2017/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-me-highgamma2017/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-me-ofner2017/README.md b/tasks/eeg/eeg-me-ofner2017/README.md index 35c1fc4a36916fba004f6757c831cd739f8cce7e..eed49429e8f865b43c66ec83072808f796052c88 100644 --- a/tasks/eeg/eeg-me-ofner2017/README.md +++ b/tasks/eeg/eeg-me-ofner2017/README.md @@ -1,32 +1,29 @@ # Ofner2017 motor-execution classification -[Task catalog](../../../README.md) +This Ofner2017 task asks an agent to classify three-second motor-execution EEG windows into seven native classes. Training and validation use different subjects. -Ofner2017 motor execution; frozen motor_execution/ofner2017 protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-me-ofner2017` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `motor_execution/ofner2017` (`ofner2017-execution`) | +| EEG input | 61 channels · 120 Hz · 3 s · `[61, 360]` samples | +| Public windows | 3,780 train · 1,260 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 7 native classes · normalized probabilities `[B, 7]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-me-ofner2017/public) contains 4 files (443,100,882 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-me-ofner2017/public) contains 4 files (443,100,882 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-me-ofner2017/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-me-ofner2017/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-me-ofner2017/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-me-ofner2017/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-mental-arithmetic-zyma2019/README.md b/tasks/eeg/eeg-mental-arithmetic-zyma2019/README.md index 469443338b39e1a890ace971e20bc9915cbd1b9a..24c492109ece45ec0d4557a379ae4f73d9fca55e 100644 --- a/tasks/eeg/eeg-mental-arithmetic-zyma2019/README.md +++ b/tasks/eeg/eeg-mental-arithmetic-zyma2019/README.md @@ -1,32 +1,29 @@ # Zyma2019 mental-arithmetic classification -[Task catalog](../../../README.md) +This Zyma2019 task classifies five-second mental-arithmetic EEG windows into two native classes. Its public validation split is subject-disjoint. -Zyma mental arithmetic; frozen mental_arithmetic/default protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-mental-arithmetic-zyma2019` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `mental_arithmetic/default` (`Zyma2019Electroencephalograms`) | +| EEG input | 20 channels · 120 Hz · 5 s · `[20, 600]` samples | +| Public windows | 986 train · 337 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 2 native classes · normalized probabilities `[B, 2]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-mental-arithmetic-zyma2019/public) contains 4 files (63,605,750 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-mental-arithmetic-zyma2019/public) contains 4 files (63,605,750 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mental-arithmetic-zyma2019/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mental-arithmetic-zyma2019/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-mental-arithmetic-zyma2019/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mental-arithmetic-zyma2019/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-mi-barachant2012/README.md b/tasks/eeg/eeg-mi-barachant2012/README.md index d74d0b77bf0319249da50879029cf6b1380c66c1..6adf6f7492e6783ac76dad38d04f2af0df4fae91 100644 --- a/tasks/eeg/eeg-mi-barachant2012/README.md +++ b/tasks/eeg/eeg-mi-barachant2012/README.md @@ -1,32 +1,29 @@ # AlexMI motor-imagery classification -[Task catalog](../../../README.md) +This AlexMI task asks an agent to classify four-second motor-imagery EEG windows into three native classes. The split separates trigger indices and excludes overlapping windows on the same timeline. -AlexMI motor imagery; frozen motor_imagery/barachant2012 protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-mi-barachant2012` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `motor_imagery/barachant2012` (`barachant2012`) | +| EEG input | 16 channels · 120 Hz · 4 s · `[16, 480]` samples | +| Public windows | 288 train · 96 validation | +| Native split | Trigger-index-disjoint native SklearnSplit. Same-timeline windows do not overlap. | +| Output | 3 native classes · normalized probabilities `[B, 3]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-mi-barachant2012/public) contains 4 files (11,825,808 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-mi-barachant2012/public) contains 4 files (11,825,808 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-barachant2012/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-barachant2012/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-mi-barachant2012/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-barachant2012/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-mi-bnci2014/README.md b/tasks/eeg/eeg-mi-bnci2014/README.md index 21c606809e11922c5ee3f7589ba439916a2f667b..9c1c81e00a5bf8380eac5955b2d71921da6a9aa0 100644 --- a/tasks/eeg/eeg-mi-bnci2014/README.md +++ b/tasks/eeg/eeg-mi-bnci2014/README.md @@ -1,32 +1,29 @@ # BCI-IV-2a native motor-imagery classification -[Task catalog](../../../README.md) +This task classifies four-second BCI-IV-2a EEG windows into four source-defined motor-imagery classes. It retains the native subject grouping from the frozen AgentEEGBench protocol. It is not the legacy `bciciv-2a` task, which fits session T and scores session E per subject. -BCI-IV-2a native subject-grouped motor-imagery task, shared with AgentEEGBench. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-mi-bnci2014` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `motor_imagery/tangermann2012` · BCI-IV-2a | +| EEG input | 22 channels · 120 Hz · 4 s · `[22, 480]` samples | +| Public windows | 2,880 train · 1,152 validation | +| Native split | Subject-grouped · distinct from the legacy session T/E protocol | +| Output | 4 native classes · normalized probabilities `[B, 4]` | +| Metric | Public balanced accuracy (maximize) · task-specific scorer | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-mi-bnci2014/public) contains 2 files (170,344,916 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-mi-bnci2014/public) contains 2 files (170,344,916 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-bnci2014/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-bnci2014/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-mi-bnci2014/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-bnci2014/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-mi-cho2017/README.md b/tasks/eeg/eeg-mi-cho2017/README.md index f0624d1e4f035741d9180f3f43e7516430adef54..8980a7f9c9a085b46d0285aca0b332b730e2ee6e 100644 --- a/tasks/eeg/eeg-mi-cho2017/README.md +++ b/tasks/eeg/eeg-mi-cho2017/README.md @@ -1,32 +1,29 @@ # Cho2017 motor-imagery classification -[Task catalog](../../../README.md) +This Cho2017 task classifies four-second motor-imagery EEG windows into two native classes. The source protocol reserves separate subjects for validation. -Cho2017 motor imagery; frozen motor_imagery/cho2017 protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-mi-cho2017` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `motor_imagery/cho2017` (`cho2017`) | +| EEG input | 64 channels · 120 Hz · 4 s · `[64, 480]` samples | +| Public windows | 6,120 train · 2,200 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 2 native classes · normalized probabilities `[B, 2]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-mi-cho2017/public) contains 4 files (1,023,001,442 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-mi-cho2017/public) contains 4 files (1,023,001,442 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-cho2017/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-cho2017/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-mi-cho2017/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-cho2017/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-mi-eegmmidb/README.md b/tasks/eeg/eeg-mi-eegmmidb/README.md index b2c521bd901b8f1bcabd4eece0a4c19439f0e198..6d0a5ac114cbf017a26b3d06bd1968af2b3eb257 100644 --- a/tasks/eeg/eeg-mi-eegmmidb/README.md +++ b/tasks/eeg/eeg-mi-eegmmidb/README.md @@ -1,32 +1,29 @@ # EEGMMIDB motor-imagery classification -[Task catalog](../../../README.md) +This EEGMMIDB task uses four-second motor-imagery EEG windows and four native classes. Training and validation subjects do not overlap. -EEGMMIDB motor imagery; frozen motor_imagery/schalk2004bci2000 protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-mi-eegmmidb` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `motor_imagery/schalk2004bci2000` (`schalk2004-eegmmidb`) | +| EEG input | 64 channels · 120 Hz · 4 s · `[64, 480]` samples | +| Public windows | 5,670 train · 1,888 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 4 native classes · normalized probabilities `[B, 4]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-mi-eegmmidb/public) contains 4 files (929,308,208 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-mi-eegmmidb/public) contains 4 files (929,308,208 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-eegmmidb/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-eegmmidb/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-mi-eegmmidb/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-eegmmidb/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-mi-openbmi2019/README.md b/tasks/eeg/eeg-mi-openbmi2019/README.md index 8821dc1ac687f2c480879df4f53170a228d741b6..bfc311b00e53e0f5c6e82c03d66cd74f6c4b0717 100644 --- a/tasks/eeg/eeg-mi-openbmi2019/README.md +++ b/tasks/eeg/eeg-mi-openbmi2019/README.md @@ -1,32 +1,29 @@ # OpenBMI motor-imagery classification -[Task catalog](../../../README.md) +This OpenBMI motor-imagery task asks an agent to classify four-second EEG windows into two native classes. Its native split keeps validation subjects out of training. -OpenBMI motor imagery; frozen motor_imagery/lee2019mi protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-mi-openbmi2019` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `motor_imagery/lee2019mi` (`OpenBMI_Lee2019`) | +| EEG input | 62 channels · 120 Hz · 4 s · `[62, 480]` samples | +| Public windows | 6,400 train · 2,200 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 2 native classes · normalized probabilities `[B, 2]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-mi-openbmi2019/public) contains 4 files (1,024,405,402 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-mi-openbmi2019/public) contains 4 files (1,024,405,402 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-openbmi2019/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-openbmi2019/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-mi-openbmi2019/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-openbmi2019/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-mi-zhou2016/README.md b/tasks/eeg/eeg-mi-zhou2016/README.md index bec0eee36f2a6c809d2165ebe0c9648d7a8904d8..9fe4a7fe4ae3b3e0f59b34effc3adeaeb1c3e0d5 100644 --- a/tasks/eeg/eeg-mi-zhou2016/README.md +++ b/tasks/eeg/eeg-mi-zhou2016/README.md @@ -1,32 +1,29 @@ # Zhou2016 motor-imagery classification -[Task catalog](../../../README.md) +This Zhou2016 task classifies four-second motor-imagery EEG windows into three native classes. The source protocol places training and validation in separate sessions. -Zhou2016 motor imagery; frozen motor_imagery/zhou2016 protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-mi-zhou2016` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `motor_imagery/zhou2016` (`zhou2016`) | +| EEG input | 14 channels · 120 Hz · 4 s · `[14, 480]` samples | +| Public windows | 614 train · 586 validation | +| Native split | Session-disjoint native PredefinedSplit. | +| Output | 3 native classes · normalized probabilities `[B, 3]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-mi-zhou2016/public) contains 4 files (32,355,620 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-mi-zhou2016/public) contains 4 files (32,355,620 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-zhou2016/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-zhou2016/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-mi-zhou2016/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-mi-zhou2016/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-p3-openbmi2019/README.md b/tasks/eeg/eeg-p3-openbmi2019/README.md index 1066190def5d89f55acfb14b9768ffa5be65c757..4287b4e35ff802a843bce7e059ce07906b62ea73 100644 --- a/tasks/eeg/eeg-p3-openbmi2019/README.md +++ b/tasks/eeg/eeg-p3-openbmi2019/README.md @@ -1,32 +1,29 @@ # OpenBMI P3 EEG classification -[Task catalog](../../../README.md) +This OpenBMI P3 task uses one-second EEG windows and two native classes. Training and validation use disjoint subjects under the source protocol. -OpenBMI P3; frozen p3/lee2019erp protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-p3-openbmi2019` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `p3/lee2019erp` (`OpenBMI_Lee2019`) | +| EEG input | 62 channels · 120 Hz · 1 s · `[62, 120]` samples | +| Public windows | 264,960 train · 91,080 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 2 native classes · normalized probabilities `[B, 2]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-p3-openbmi2019/public) contains 4 files (10,623,665,898 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-p3-openbmi2019/public) contains 4 files (10,623,665,898 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-p3-openbmi2019/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-p3-openbmi2019/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-p3-openbmi2019/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-p3-openbmi2019/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-sleep-stage-sleepedf/README.md b/tasks/eeg/eeg-sleep-stage-sleepedf/README.md index ec41307af3905bad0fd9d1ad08d923a676dfec95..cb41ec87be84f5551aeb94d9e3b319eb4e396efb 100644 --- a/tasks/eeg/eeg-sleep-stage-sleepedf/README.md +++ b/tasks/eeg/eeg-sleep-stage-sleepedf/README.md @@ -1,32 +1,29 @@ # Sleep-EDF cassette sleep-stage classification -[Task catalog](../../../README.md) +This task classifies 30-second Sleep-EDF cassette EEG windows into N1, N2, N3, R, and W. It uses a full native export from 78 subjects. The native pipeline crops wake time to 30 minutes and uses a subject-disjoint split. -Sleep-EDF full native subject-disjoint sleep staging with public train/validation; two EEG channels, 30-second windows, and five-class balanced accuracy. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-sleep-stage-sleepedf` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `sleep_stage/default` from `Kemp2000Analysis` | +| EEG input | 2 channels · 120 Hz · 30 s · `[2, 3600]` samples | +| Public windows | 116,493 train · 38,071 validation | +| Native split | Subject-disjoint `SklearnSplit` · 78 source subjects | +| Output | 5 class probabilities · N1=0, N2=1, N3=2, R=3, W=4 | +| Metric | Five-class balanced accuracy (maximize) · complete-class profile | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-sleep-stage-sleepedf/public) contains 4 files (4,453,124,284 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-sleep-stage-sleepedf/public) contains 4 files (4,453,124,284 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-sleep-stage-sleepedf/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-sleep-stage-sleepedf/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-sleep-stage-sleepedf/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-sleep-stage-sleepedf/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-ssvep-openbmi2019/README.md b/tasks/eeg/eeg-ssvep-openbmi2019/README.md index b1190744f9f6a7b35b2c259e7231043326192e9c..eb28e64551e2c43e88293cfdf10fe798e3fa6895 100644 --- a/tasks/eeg/eeg-ssvep-openbmi2019/README.md +++ b/tasks/eeg/eeg-ssvep-openbmi2019/README.md @@ -1,32 +1,29 @@ # OpenBMI SSVEP classification -[Task catalog](../../../README.md) +This OpenBMI SSVEP task asks an agent to classify four-second EEG windows into four native classes. The public validation subjects are separate from training subjects. -OpenBMI SSVEP; frozen ssvep/lee2019ssvep protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-ssvep-openbmi2019` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `ssvep/lee2019ssvep` (`OpenBMI_Lee2019`) | +| EEG input | 62 channels · 120 Hz · 4 s · `[62, 480]` samples | +| Public windows | 6,400 train · 2,200 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 4 native classes · normalized probabilities `[B, 4]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-ssvep-openbmi2019/public) contains 4 files (1,024,405,402 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-ssvep-openbmi2019/public) contains 4 files (1,024,405,402 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-ssvep-openbmi2019/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-ssvep-openbmi2019/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-ssvep-openbmi2019/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-ssvep-openbmi2019/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-ssvep-wang2017/README.md b/tasks/eeg/eeg-ssvep-wang2017/README.md index 243532f299583af120c889a2343fc65762269263..ade207ba32f5549f4bb5cbefca674d880cac7145 100644 --- a/tasks/eeg/eeg-ssvep-wang2017/README.md +++ b/tasks/eeg/eeg-ssvep-wang2017/README.md @@ -1,32 +1,29 @@ # Wang2017 SSVEP classification -[Task catalog](../../../README.md) +This Wang2017 SSVEP task classifies four-second EEG windows into 40 native classes. The native split evaluates the chosen method on different subjects. -Wang2017 SSVEP; frozen ssvep/default protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-ssvep-wang2017` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `ssvep/default` (`wang2017`) | +| EEG input | 64 channels · 120 Hz · 4 s · `[64, 480]` samples | +| Public windows | 4,800 train · 1,680 validation | +| Native split | Subject-disjoint native SklearnSplit. | +| Output | 40 native classes · normalized probabilities `[B, 40]` | +| Metric | Balanced accuracy (maximize). Complete-class per-class recall. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-ssvep-wang2017/public) contains 4 files (796,760,562 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-ssvep-wang2017/public) contains 4 files (796,760,562 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-ssvep-wang2017/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-ssvep-wang2017/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-ssvep-wang2017/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-ssvep-wang2017/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/eeg-typing-spanishbcbl/README.md b/tasks/eeg/eeg-typing-spanishbcbl/README.md index 8a4c85fe6c0f728e7365ec453efa8ce9ecb90816..dfe1b9642f10000b0b632027ff5053860d3816c9 100644 --- a/tasks/eeg/eeg-typing-spanishbcbl/README.md +++ b/tasks/eeg/eeg-typing-spanishbcbl/README.md @@ -1,32 +1,29 @@ # SpanishBCBL EEG typing classification -[Task catalog](../../../README.md) +This task classifies one-second typing-related EEG windows into 29 source-defined output classes. The mapping includes characters, space, a number group, and a special-symbol group. The native SimilaritySplit separates train and validation by sentence-similarity clusters. -SpanishBCBL EEG typing; frozen typing/default protocol adapted for public train/valid model validation. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `eeg-typing-spanishbcbl` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Scientific data | `typing/default` (`Levy2026NoninvasiveEeg`) | +| EEG input | 61 channels · 120 Hz · 1 s · `[61, 120]` samples | +| Public windows | 87,656 train · 32,909 validation | +| Native split | Sentence-similarity cluster-disjoint native SimilaritySplit. | +| Output | 29 native classes · normalized probabilities `[B, 29]` | +| Metric | Balanced accuracy (maximize). Sparse macro over observed true or predicted classes. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-typing-spanishbcbl/public) contains 4 files (3,539,526,604 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/eeg-typing-spanishbcbl/public) contains 4 files (3,539,526,604 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-typing-spanishbcbl/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-typing-spanishbcbl/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/eeg-typing-spanishbcbl/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/eeg-typing-spanishbcbl/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/eeg/sleep-edf/README.md b/tasks/eeg/sleep-edf/README.md index ac987f7b6c7c00a4e1dbd7eb4670780474ad68ed..710dbfb9ca205e4feb4685b77c3636bded643151 100644 --- a/tasks/eeg/sleep-edf/README.md +++ b/tasks/eeg/sleep-edf/README.md @@ -1,32 +1,26 @@ # sleep-edf — 5-class Sleep Staging (Sleep-EDF Cassette) -[Task catalog](../../../README.md) +The agent designs a PyTorch `nn.Module` **SleepAgentModel** that classifies a `(B, 1, 3000)` tensor of preprocessed Fpz-Cz sleep EEG (30 s epoch at 100 Hz, microvolts) into 5 sleep stages (Wake / N1 / N2 / N3 / REM). -5-class sleep-staging on Sleep-EDF Cassette (20 subjects, single-channel Fpz-Cz EEG, 30 s epochs → Wake / N1 / N2 / N3 / REM). Subjects 0-13 are the training pool, 14-15 are validation, and 16-19 are the private held-out test set. The agent submits a PyTorch `SleepAgentModel` class (no direct reuse of prebuilt sleep-staging models); the scorer trains one shared model with class-weighted CE and early stopping, then blind-tests on subjects 16-19, reporting Cohen's kappa (primary) alongside accuracy / balanced accuracy / macro F1 / per-class recall. +Historical Agent results for this retained task are recorded in the v0 report. -Historical results for this retained task remain in the v0 report. +## Task at a glance -## Task and data - -| Field | Value | +| Field | Task contract | |---|---| -| Task ID | `sleep-edf` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2` | -| Data category | EEG | -| Access | `hosted_public` | -| Primary metric | `See task protocol` (See task protocol) | - -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/sleep-edf/public) contains 2 files (1,225,526,664 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. - -## Protocol and source +| Input | Fpz-Cz sleep EEG: a 30-second, 100 Hz epoch shaped `(B, 1, 3000)`. | +| Output | One of five sleep stages: Wake, N1, N2, N3, or REM. | +| Split | Subjects 0–13 train the model; 14–15 support early stopping; 16–19 are private Test. | +| Metric | `test_kappa` across subjects 16–19; the leaderboard `score` clips it to `[0,1]`. | -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/sleep-edf/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Data access -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/sleep-edf/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/eeg/sleep-edf/public) contains 2 files (1,225,526,664 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. Original source terms apply. This catalog does not relicense the data. + +## Protocol and source + +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/eeg/sleep-edf/README.md) defines the scientific protocol, preparation, and scoring. + +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/eeg/sleep-edf/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/invasive/falcon-b1-birdsong/README.md b/tasks/invasive/falcon-b1-birdsong/README.md index ddcaf9d39567d56768f40b14a4d262530fa5f1e6..70cf9575b60d865888a08e1a4b29babc0d291ab7 100644 --- a/tasks/invasive/falcon-b1-birdsong/README.md +++ b/tasks/invasive/falcon-b1-birdsong/README.md @@ -1,34 +1,32 @@ # B1: birdsong spectrogram -[Task catalog](../../../README.md) +A Neuropixels probe recorded 85 threshold-crossing channels from a singing zebra finch. The task predicts one vocalization spectrogram for each complete song motif. It is not a human speech task. -Predict a zebra finch vocalization spectrogram from one complete motif of intracortical threshold crossings at a time. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | +| Field | Task contract | |---|---| -| Task ID | `falcon-b1-birdsong` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation-motif` | -| Data category | Invasive recordings | -| Access | `hosted_public` | -| Primary metric | `normalized_spectrogram_MSE` (minimize) | +| Input | One `float32[27000,85]` neural motif: 900 ms sampled at 30 kHz. | +| Output | One finite `float32[880,158]` vocalization spectrogram per motif. | +| Split | Two earlier recording dates for Train, the last held-in date for Valid, and three calibration dates for evaluator-only Test. | +| Metric | Native-mask normalized spectrogram MSE per motif, then the equal-weight date mean. Lower is better. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/invasive/falcon-b1-birdsong/public) contains 11 files (170,230,855 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +| Role | Dates | Complete motifs | Neural samples | +|---|---:|---:|---:| +| Train | 2 | 40 | 1,080,000 | +| Valid | 1 | 8 | 216,000 | +| Evaluator-only Test | 3 | 9 | 243,000 | -This task uses a BrainPilotBench date split. Its scores are not official FALCON leaderboard scores. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/invasive/falcon-b1-birdsong/public) contains 11 files (170,230,855 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +The DANDI record lists CC BY 4.0. See the source attribution and notice of transformations. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/intracortical/falcon-b1-birdsong/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://dandiarchive.org/dandiset/001046/draft) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/intracortical/falcon-b1-birdsong/README.md) defines the scientific protocol, preparation, and scoring. -The DANDI record lists CC BY 4.0. See the source attribution and notice of transformations. +[Source record](https://dandiarchive.org/dandiset/001046/draft) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/invasive/falcon-h1-reach-grasp/README.md b/tasks/invasive/falcon-h1-reach-grasp/README.md index c9f9212e7242df1764bcb29efabcf04dae2ab336..47cae5f331162fcb73f5fb5bff0cf8c78d759076 100644 --- a/tasks/invasive/falcon-h1-reach-grasp/README.md +++ b/tasks/invasive/falcon-h1-reach-grasp/README.md @@ -1,33 +1,32 @@ # H1: attempted reach and grasp -[Task catalog](../../../README.md) +A human participant watched a virtual arm and attempted arm and grasp movements. Utah arrays recorded threshold crossings in motor cortex. The task predicts seven commanded velocities, not measured arm movement. Read the [FALCON dataset description](https://snel-repo.github.io/falcon/datasets.html) and the [native loader](https://github.com/snel-repo/falcon-challenge/blob/770c9b9597b8f58bf67b5a9ec6401ef705a2cb0f/falcon_challenge/dataloaders.py#L93-L106). -Develop a causal intracortical decoder for seven attempted arm and grasp velocities, with chronological training and public validation on a later recording date. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | +| Field | Task contract | |---|---| -| Task ID | `falcon-h1-reach-grasp` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation-stream` | -| Data category | Invasive recordings | -| Access | `source_only` | -| Primary metric | `R2_variance_weighted` (maximize) | +| Input | One current float32[176] threshold-crossing bin every 20 ms, with a trial-start marker. | +| Output | Finite float32[7] commanded velocity components for the current bin. | +| Split | Five earlier source dates for Train, one held-in date for Valid, and seven later calibration dates for evaluator-only Test. | +| Metric | Native-mask R2_variance_weighted per date, then the equal-weight mean across dates. Higher is better. | -This task uses source download and local preparation. No source or derived H1 arrays are hosted here. -Read and comply with the [source agreement](https://dandiarchive.org/dandiset/000954/draft) before download. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/intracortical/falcon-h1-reach-grasp/README.md) defines the exact date split and local build commands. +| Role | Source date IDs | Files | +|---|---|---:| +| Train | 19250101, 19250108, 19250113, 19250115, 19250119 | 11 | +| Valid | 19250120 | 2 | +| Evaluator-only Test | 19250126, 19250127, 19250129, 19250202, 19250203, 19250206, 19250209 | 14 | -This task uses a BrainPilotBench date split. Its scores are not official FALCON leaderboard scores. +## Data access -## Protocol and source +This task uses source download and local preparation. No H1 source or derived arrays are hosted here. Read the [source agreement](https://dandiarchive.org/dandiset/000954/draft) before download. + +The source description prohibits redistribution under a Data Use Agreement. No H1 data are mirrored. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/intracortical/falcon-h1-reach-grasp/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://dandiarchive.org/dandiset/000954/draft) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/intracortical/falcon-h1-reach-grasp/README.md) defines the scientific protocol, preparation, and scoring. -The source description prohibits redistribution under a Data Use Agreement. No H1 data are mirrored. +[Source record](https://dandiarchive.org/dandiset/000954/draft) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/invasive/falcon-h2-handwriting/README.md b/tasks/invasive/falcon-h2-handwriting/README.md index 1f170cbda844dc701ec50a4994f191d9159e29dd..293b7f79d6ecd93286e233e9ad9e544604f866c9 100644 --- a/tasks/invasive/falcon-h2-handwriting/README.md +++ b/tasks/invasive/falcon-h2-handwriting/README.md @@ -1,34 +1,32 @@ # H2: attempted handwriting -[Task catalog](../../../README.md) +A BrainGate2 participant attempted to write prompted English sentences while intracortical arrays recorded spike counts. The task decodes one sentence after each complete trial. -Develop a streaming decoder for attempted handwriting from intracortical activity and return one English sentence at each complete trial boundary. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | +| Field | Task contract | |---|---| -| Task ID | `falcon-h2-handwriting` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation-stream` | -| Data category | Invasive recordings | -| Access | `hosted_public` | -| Primary metric | `WER` (minimize) | +| Input | One current mask-selected `float32[192]` neural bin per call. Bins are 20 ms apart and mark trial starts. | +| Output | One UTF-8 sentence string of at most 2,048 bytes after each complete trial. | +| Split | 20 earlier recording dates for Train, one later held-in date for Valid, and five calibration dates for evaluator-only Test. | +| Metric | Word error rate (WER) per date, then the equal-weight date mean. Lower is better. Character error rate (CER) is secondary. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/invasive/falcon-h2-handwriting/public) contains 86 files (1,110,017,522 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +| Role | Dates | Complete trials | Neural bins | +|---|---:|---:|---:| +| Train | 20 | 647 | 1,397,554 | +| Valid | 1 | 24 | 43,929 | +| Evaluator-only Test | 5 | 15 | 22,712 | -This task uses a BrainPilotBench date split. Its scores are not official FALCON leaderboard scores. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/invasive/falcon-h2-handwriting/public) contains 86 files (1,110,017,522 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +The DANDI record lists CC BY 4.0. See the source attribution and notice of transformations. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/intracortical/falcon-h2-handwriting/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://dandiarchive.org/dandiset/000950/0.241029.1403) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/intracortical/falcon-h2-handwriting/README.md) defines the scientific protocol, preparation, and scoring. -The DANDI record lists CC BY 4.0. See the source attribution and notice of transformations. +[Source record](https://dandiarchive.org/dandiset/000950/0.241029.1403) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/invasive/falcon-m1-emg/README.md b/tasks/invasive/falcon-m1-emg/README.md index 093c57fed9b07f43b20d7c53a5934fb582d16d9b..23fd7ffde87669631ac65c43c912217fd47422a6 100644 --- a/tasks/invasive/falcon-m1-emg/README.md +++ b/tasks/invasive/falcon-m1-emg/README.md @@ -1,34 +1,26 @@ # M1-A: upper-limb EMG -[Task catalog](../../../README.md) +This task predicts 16 upper-limb muscle signals from 64 intracortical channels during macaque reach and grasp. -Develop a causal 64-channel decoder for 16 upper-limb EMG signals. Train on earlier M1-A dates and validate on the final held-in date. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | +| Field | Task contract | |---|---| -| Task ID | `falcon-m1-emg` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation-stream` | -| Data category | Invasive recordings | -| Access | `hosted_public` | -| Primary metric | `R2_variance_weighted` (maximize) | +| Input | One current `float32[64]` neural bin per call, with a trial-start marker. Bins are 20 ms apart. | +| Output | Finite `float32[16]` preprocessed EMG values for the current bin. | +| Split | Three earlier recording dates for Train, one date for Valid, and three later dates for evaluator-only Test. | +| Metric | Native-mask variance-weighted R² for each date, then the equal-weight mean across dates. Higher is better. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/invasive/falcon-m1-emg/public) contains 18 files (134,424,422 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -This task uses a BrainPilotBench date split. Its scores are not official FALCON leaderboard scores. +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/invasive/falcon-m1-emg/public) contains 18 files (134,424,422 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. -## Protocol and source +The DANDI record lists CC BY 4.0. See the source attribution and notice of transformations. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/intracortical/falcon-m1-emg/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://dandiarchive.org/dandiset/000941/0.241029.1405) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/intracortical/falcon-m1-emg/README.md) defines the scientific protocol, preparation, and scoring. -The DANDI record lists CC BY 4.0. See the source attribution and notice of transformations. +[Source record](https://dandiarchive.org/dandiset/000941/0.241029.1405) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/invasive/falcon-m2-finger-velocity/README.md b/tasks/invasive/falcon-m2-finger-velocity/README.md index 2940b1f8142336ffc61592ad61009aaa27c4fa7e..a291adaaeca8448a083cd1be5808ef78f0afed0c 100644 --- a/tasks/invasive/falcon-m2-finger-velocity/README.md +++ b/tasks/invasive/falcon-m2-finger-velocity/README.md @@ -1,34 +1,26 @@ # M2: finger-group velocity -[Task catalog](../../../README.md) +This task predicts two finger-group velocities from 96 macaque intracortical channels during finger control. -Develop a causal 96-channel decoder for two finger-group velocities. Train on earlier M2 dates and validate on the final held-in date. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | +| Field | Task contract | |---|---| -| Task ID | `falcon-m2-finger-velocity` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation-stream` | -| Data category | Invasive recordings | -| Access | `hosted_public` | -| Primary metric | `R2_variance_weighted` (maximize) | +| Input | One current `float32[96]` neural bin per call, with a trial-start marker. Bins are 20 ms apart. | +| Output | Finite `float32[2]` finger-group velocities for the current bin. | +| Split | Three earlier recording dates for Train, one date for Valid, and four later dates for evaluator-only Test. | +| Metric | Native-mask variance-weighted R² for each date, then the equal-weight mean across dates. Higher is better. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/invasive/falcon-m2-finger-velocity/public) contains 30 files (13,234,392 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -This task uses a BrainPilotBench date split. Its scores are not official FALCON leaderboard scores. +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/invasive/falcon-m2-finger-velocity/public) contains 30 files (13,234,392 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. -## Protocol and source +The DANDI record lists CC BY 4.0. See the source attribution and notice of transformations. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/intracortical/falcon-m2-finger-velocity/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://dandiarchive.org/dandiset/000953/draft) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/intracortical/falcon-m2-finger-velocity/README.md) defines the scientific protocol, preparation, and scoring. -The DANDI record lists CC BY 4.0. See the source attribution and notice of transformations. +[Source record](https://dandiarchive.org/dandiset/000953/draft) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/invasive/ieeg-film-speech-music/README.md b/tasks/invasive/ieeg-film-speech-music/README.md index 0cc6791e15953963bfb243ea54ba6b5ee53ba9cc..8cd47429d94427413f03aebd43dd86a59733c5c0 100644 --- a/tasks/invasive/ieeg-film-speech-music/README.md +++ b/tasks/invasive/ieeg-film-speech-music/README.md @@ -1,35 +1,28 @@ # Film speech versus music from clinical iEEG -[Task catalog](../../../README.md) +This task classifies speech and music intervals in a film from clinical ECoG and sEEG recordings. It tests held-out film blocks within each participant. -Predict speech or music from independent clinical iEEG windows in unseen segments of the same film for each participant. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | +| Field | Task contract | |---|---| -| Task ID | `ieeg-film-speech-music` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-complete-guarded-windows` | -| Data category | Invasive recordings | -| Access | `hosted_public` | -| Primary metric | `balanced_accuracy` (maximize) | +| Input | One `float32[channels,512]` two-second neural window and an opaque participant ID. | +| Output | One finite `float32` speech probability in `[0,1]` for each window. | +| Split | Global film blocks: Train 1, 3, 6, 7, 8, 10, 13. Valid 4, 11. Evaluator-only Test 2, 5, 9, 12. | +| Metric | Average window probabilities within each block. Compute balanced accuracy per participant, then average participants equally. Higher is better. | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/invasive/ieeg-film-speech-music/public) contains 257 files (922,341,200 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -The public package supports Agent preparation. Block-first scoring still requires the trusted evaluator mapping. -The package excludes the movie, owner mapping, shuffle key, and Test data. +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/invasive/ieeg-film-speech-music/public) contains 257 files (922,341,200 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. -## Protocol and source +The public package supports Agent preparation. Block-first scoring requires the trusted evaluator’s owner mapping. That mapping is not public. + +The pinned OpenNeuro metadata lists CC0. The copyrighted film is excluded. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/ieeg/ieeg-film-speech-music/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://doi.org/10.18112/openneuro.ds003688.v1.0.7) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/ieeg/ieeg-film-speech-music/README.md) defines the scientific protocol, preparation, and scoring. -The pinned OpenNeuro metadata lists CC0. The copyrighted film is excluded. +[Source record](https://doi.org/10.18112/openneuro.ds003688.v1.0.7) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/invasive/ieeg-finger-flexion-bciciv4/README.md b/tasks/invasive/ieeg-finger-flexion-bciciv4/README.md index e3d8b663decb60a4f832e88350ad2dbac5f55b4e..8abed0327a4db912e52d79d6909f781ca90a6e58 100644 --- a/tasks/invasive/ieeg-finger-flexion-bciciv4/README.md +++ b/tasks/invasive/ieeg-finger-flexion-bciciv4/README.md @@ -1,36 +1,26 @@ # BCI Competition IV Dataset 4: finger flexion -[Task catalog](../../../README.md) +This task predicts continuous finger flexion from ECoG recordings in three participants. Each model returns five trajectories, while the score uses four fingers. -Predict five finger-flexion trajectories from human ECoG in three participants, with chronological public validation and a guarded within-participant split. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | +| Field | Task contract | |---|---| -| Task ID | `ieeg-finger-flexion-bciciv4` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation-offline` | -| Data category | Invasive recordings | -| Access | `hosted_public` | -| Primary metric | `pearson_r` (maximize) | - -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/invasive/ieeg-finger-flexion-bciciv4/public) contains 14 files (324,773,839 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. - -Train uses samples `[0,319000)` and Valid uses `[321000,400000)` for all three participants. -The 2,000-sample guard and original 200,000-sample evaluation interval remain outside these public files. -The mean Pearson correlation scores thumb, index, middle, and little finger. Predictions retain five columns. - -## Protocol and source +| Input | Offline `float32[T,C]` ECoG interval. `C` is 62, 48, or 64 channels for `sub1`, `sub2`, or `sub3`. | +| Output | Finite `float32[T,5]` flexion in thumb, index, middle, ring, little-finger order at 1000 Hz. | +| Split | For each participant, Train `[0,319000)` and Valid `[321000,400000)`. A 2,000-sample guard separates them. Original evaluation input stays outside this task's public export. | +| Metric | Mean Pearson `r` across thumb, index, middle, and little finger for all three participants: 12 correlations, higher is better. | -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/ieeg/ieeg-finger-flexion-bciciv4/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Data access -[Source reference](https://www.bbci.de/competition/iv/) · [Source attribution](../../../ATTRIBUTION.md) +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/invasive/ieeg-finger-flexion-bciciv4/public) contains 14 files (324,773,839 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. Original competition attribution, citation, and publication-notification terms apply. No CC or Apache data license is asserted. + +## Protocol and source + +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/ieeg/ieeg-finger-flexion-bciciv4/README.md) defines the scientific protocol, preparation, and scoring. + +[Source record](https://www.bbci.de/competition/iv/) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/mri/brain-age-mri/README.md b/tasks/mri/brain-age-mri/README.md index 457943bfcabde4d1fae21227886614b5ecb3f24b..791a19ed49fcdbb8b41ded6b5560ec7e0f565023 100644 --- a/tasks/mri/brain-age-mri/README.md +++ b/tasks/mri/brain-age-mri/README.md @@ -1,32 +1,28 @@ # Age Prediction from Structural MRI -[Task catalog](../../../README.md) +The agent develops a model that predicts chronological age from T1-weighted brain MRI. Model development uses public images and age labels. Evaluation uses a separate set of held-out subjects. -Predict chronological age from anonymized T1-weighted structural MRI. Build and freeze a model using 449 public subjects; the evaluator runs the submitted inference entry on 112 held-out images and computes subject-level MAE. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | +| Field | Details | |---|---| | Task ID | `brain-age-mri` | -| Collection | BrainPilotBench v1 | | Task version | `0.1-candidate` | -| Data category | MRI | -| Access | `hosted_public` | -| Primary metric | `test_mae` (minimize) | +| Public data | MRI scans and chronological ages for 449 subjects | +| Submission | A saved model, inference code, training code/configuration, public validation predictions, and a report | +| Primary metric | Mean absolute error in years (`test_mae`), lower is better | +| Evaluation | 112 held-out subjects with evaluator-controlled age labels | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/mri/brain-age-mri/public) contains 1 files (3,729,262,581 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/mri/brain-age-mri/public) contains 1 file (3,729,262,581 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/mri/brain-age-mri/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/mri/brain-age-mri/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/mri/brain-age-mri/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/mri/brain-age-mri/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/mri/tops-fmri/README.md b/tasks/mri/tops-fmri/README.md index 96bc43fd0e1b03065a3813572e3856662a5d5f49..8028369570babf8384265ede60d4018b8c086838 100644 --- a/tasks/mri/tops-fmri/README.md +++ b/tasks/mri/tops-fmri/README.md @@ -1,32 +1,26 @@ # tops-fmri — Tonic Pain Signature (linear FC, external validation) -[Task catalog](../../../README.md) +The agent trains a **linear** 279 ROI / 38781 edge functional-connectivity signature on the public **Study3** fMRI dynamic-FC data (`dfc_5bin_dat` × `CAPS/REST` + pain ratings). -用公开 Study3 fMRI dynamic-FC 训练一个 279 ROI / 38781 edge 的**线性** tonic-pain connectivity signature,提交权重 w_raw/b_raw 和 numpy-only apply_signature.py; benchmark 平台**私下**用 Study4/Study5 held-out features + labels 计算 Pearson r / AUC,聚合 0-1 分。agent 无法接触 held-out labels(工作区隔离 + scorer only)。 +Historical Agent results for this retained task are recorded in the v0 report. -Historical results for this retained task remain in the v0 report. +## Task at a glance -## Task and data - -| Field | Value | +| Field | Task contract | |---|---| -| Task ID | `tops-fmri` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1` | -| Data category | MRI | -| Access | `hosted_public` | -| Primary metric | `See task protocol` (See task protocol) | - -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/mri/tops-fmri/public) contains 2 files (965,667,246 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. - -## Protocol and source +| Input | Public Study3 fMRI dynamic functional connectivity: 279 ROIs, 38,781 edges, and pain ratings. | +| Output | A linear connectivity signature with saved weights and a NumPy inference script. | +| Evaluation | Study3 supports public development. Private Study4 and Study5 supply external evaluation labels. | +| Metric | `score = 0.5·study4_score + 0.5·study5_score`; Study4 uses Pearson `r`, and Study5 uses AUC. | -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/mri/tops-fmri/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Data access -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/mri/tops-fmri/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/mri/tops-fmri/public) contains 2 files (965,667,246 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. Original source terms apply. This catalog does not relicense the data. + +## Protocol and source + +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/mri/tops-fmri/README.md) defines the scientific protocol, preparation, and scoring. + +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/mri/tops-fmri/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-badham2017deficits-exp1/README.md b/tasks/psychology/psych101-badham2017deficits-exp1/README.md index c7d5499f410bc43056a1e7214f63507a4a70fba5..5d8058acce4e839eb08494576c6292f475bb5324 100644 --- a/tasks/psychology/psych101-badham2017deficits-exp1/README.md +++ b/tasks/psychology/psych101-badham2017deficits-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Category Learning from Feedback -[Task catalog](../../../README.md) +Participants classify geometric objects as E or K across four rule problems and receive feedback. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for badham2017deficits/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-badham2017deficits-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `badham2017deficits/exp1.csv` | +| Public data | 68 train and 17 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-badham2017deficits-exp1/public) contains 2 files (2,304,677 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-badham2017deficits-exp1/public) contains 2 files (2,304,677 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-badham2017deficits-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-badham2017deficits-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-badham2017deficits-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-badham2017deficits-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-bahrami2020four-exp/README.md b/tasks/psychology/psych101-bahrami2020four-exp/README.md index 6aba6102547af17e46aca0bcd469501727980cfb..8fa49d013e8e8b626f889c40d0303f06bdd3229f 100644 --- a/tasks/psychology/psych101-bahrami2020four-exp/README.md +++ b/tasks/psychology/psych101-bahrami2020four-exp/README.md @@ -1,32 +1,28 @@ # Predicting Human Choices Among Four Rewards -[Task catalog](../../../README.md) +Participants repeatedly choose among four labeled options and observe the points earned. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for bahrami2020four/exp.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-bahrami2020four-exp` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `bahrami2020four/exp.csv` | +| Public data | 695 train and 174 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-bahrami2020four-exp/public) contains 2 files (5,106,777 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-bahrami2020four-exp/public) contains 2 files (5,106,777 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-bahrami2020four-exp/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-bahrami2020four-exp/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-bahrami2020four-exp/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-bahrami2020four-exp/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/README.md b/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/README.md index d6374725fb75cdeb2f51ba1afde6907253a31385..e495fe0df87c52cf7230f38d6886c42828eb83ab 100644 --- a/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/README.md +++ b/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/README.md @@ -1,32 +1,28 @@ # Human Hormone-Level Estimates from Verbal Cues -[Task catalog](../../../README.md) +Participants estimate a target hormone level from two verbally described hormone levels. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for collsiöö2023MCPL/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-collsioo2023mcpl-exp1-775cd1984f` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `collsiöö2023MCPL/exp1.csv` | +| Public data | 56 train and 14 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/public) contains 2 files (3,027,152 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/public) contains 2 files (3,027,152 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp1-775cd1984f/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/README.md b/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/README.md index a45f278fce1bfbcfb3151599e4d3d6adb64a8f0b..ab6ac3cfa02ef3cc8c1d5d34b1f513615693d0ca 100644 --- a/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/README.md +++ b/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/README.md @@ -1,32 +1,28 @@ # Human Hormone-Level Estimates from Numeric Cues -[Task catalog](../../../README.md) +Participants estimate a target hormone level from two numbered hormone levels. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for collsiöö2023MCPL/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-collsioo2023mcpl-exp2-6bd18ff5bf` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `collsiöö2023MCPL/exp2.csv` | +| Public data | 59 train and 15 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/public) contains 2 files (3,201,056 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/public) contains 2 files (3,201,056 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp2-6bd18ff5bf/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/README.md b/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/README.md index d6be0bc47b8a3ac2bfc26909735a59b91802b615..fbfba93e79f484987823139a260ef29f46c94312 100644 --- a/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/README.md +++ b/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/README.md @@ -1,32 +1,28 @@ # Human Hormone-Level Estimates from Two Cues -[Task catalog](../../../README.md) +Participants estimate a target hormone level from two verbally described hormone levels. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for collsiöö2023MCPL/exp3.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-collsioo2023mcpl-exp3-c372064286` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `collsiöö2023MCPL/exp3.csv` | +| Public data | 70 train and 18 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/public) contains 2 files (2,025,867 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/public) contains 2 files (2,025,867 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-collsioo2023mcpl-exp3-c372064286/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-cox2017information-exp1/README.md b/tasks/psychology/psych101-cox2017information-exp1/README.md index fccde877d46833dbe01bf80cda2b3a0e6d8ac4e9..01bc525c4d2560cb4cf6d82213299f138bca2af0 100644 --- a/tasks/psychology/psych101-cox2017information-exp1/README.md +++ b/tasks/psychology/psych101-cox2017information-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Recognition of Studied Word Pairs -[Task catalog](../../../README.md) +Participants study word pairs and judge whether a later pair appeared together in the study list. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for cox2017information/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-cox2017information-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `cox2017information/exp1.csv` | +| Public data | 339 train and 85 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-cox2017information-exp1/public) contains 2 files (8,684,274 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-cox2017information-exp1/public) contains 2 files (8,684,274 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-cox2017information-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-cox2017information-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-cox2017information-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-cox2017information-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/README.md b/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/README.md index 9bd266e3206ff546049b40d5888cbe2c0195ef88..540c6c2210ccb1195f428a27b63b6c0a9b9097c8 100644 --- a/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/README.md +++ b/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/README.md @@ -1,32 +1,28 @@ # Predicting Human N-Back Letter Responses -[Task catalog](../../../README.md) +Participants compare each letter with the one shown N trials earlier and press a match or nonmatch key. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for enkavi2019adaptivenback/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-enkavi2019adaptivenback-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `enkavi2019adaptivenback/exp1.csv` | +| Public data | 376 train and 94 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/public) contains 2 files (8,466,948 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/public) contains 2 files (8,466,948 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019adaptivenback-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-enkavi2019digitspan-exp1/README.md b/tasks/psychology/psych101-enkavi2019digitspan-exp1/README.md index e8523ff6ddb1fa745598947eabe7b248aa508609..b4521faf4da8c9ba5f2a9da2712a44d438063ee4 100644 --- a/tasks/psychology/psych101-enkavi2019digitspan-exp1/README.md +++ b/tasks/psychology/psych101-enkavi2019digitspan-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Digit-Sequence Recall -[Task catalog](../../../README.md) +Participants view a digit sequence and type the digits in their remembered order. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for enkavi2019digitspan/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-enkavi2019digitspan-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `enkavi2019digitspan/exp1.csv` | +| Public data | 377 train and 95 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-enkavi2019digitspan-exp1/public) contains 2 files (5,692,403 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-enkavi2019digitspan-exp1/public) contains 2 files (5,692,403 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019digitspan-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019digitspan-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-enkavi2019digitspan-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019digitspan-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-enkavi2019gonogo-exp1/README.md b/tasks/psychology/psych101-enkavi2019gonogo-exp1/README.md index 4aff6a63b0520f6b401cefa6251d2de3bbe45674..829b9f444699789fdc67b41ce915cf9f8e37cddc 100644 --- a/tasks/psychology/psych101-enkavi2019gonogo-exp1/README.md +++ b/tasks/psychology/psych101-enkavi2019gonogo-exp1/README.md @@ -1,32 +1,28 @@ # Predicting Human Go/No-Go Keypresses -[Task catalog](../../../README.md) +Participants press a key for one color and withhold a response for another color. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for enkavi2019gonogo/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-enkavi2019gonogo-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `enkavi2019gonogo/exp1.csv` | +| Public data | 370 train and 93 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-enkavi2019gonogo-exp1/public) contains 2 files (7,564,952 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-enkavi2019gonogo-exp1/public) contains 2 files (7,564,952 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019gonogo-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019gonogo-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-enkavi2019gonogo-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019gonogo-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-enkavi2019recentprobes-exp1/README.md b/tasks/psychology/psych101-enkavi2019recentprobes-exp1/README.md index 965e4a7fde26bb19450739e655bb5b66419c7031..47d33bbe6aef231f75080db1f8a7be7eaf386549 100644 --- a/tasks/psychology/psych101-enkavi2019recentprobes-exp1/README.md +++ b/tasks/psychology/psych101-enkavi2019recentprobes-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Recognition of Recent Letters -[Task catalog](../../../README.md) +Participants remember six letters and judge whether a later probe letter belonged to that list. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for enkavi2019recentprobes/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-enkavi2019recentprobes-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `enkavi2019recentprobes/exp1.csv` | +| Public data | 376 train and 95 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-enkavi2019recentprobes-exp1/public) contains 2 files (3,678,382 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-enkavi2019recentprobes-exp1/public) contains 2 files (3,678,382 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019recentprobes-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019recentprobes-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-enkavi2019recentprobes-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-enkavi2019recentprobes-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-feng2021dynamics-exp1/README.md b/tasks/psychology/psych101-feng2021dynamics-exp1/README.md index 232f8ddf3a4a6b5bacd9d824e05ece3b645b1489..2d84a89bec8686ecc0c4636409ca46ec450e2460 100644 --- a/tasks/psychology/psych101-feng2021dynamics-exp1/README.md +++ b/tasks/psychology/psych101-feng2021dynamics-exp1/README.md @@ -1,32 +1,28 @@ # Predicting Human Choices Between Changing Slot Machines -[Task catalog](../../../README.md) +Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for feng2021dynamics/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-feng2021dynamics-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `feng2021dynamics/exp1.csv` | +| Public data | 20 train and 6 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-feng2021dynamics-exp1/public) contains 2 files (3,114,689 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-feng2021dynamics-exp1/public) contains 2 files (3,114,689 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-feng2021dynamics-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-feng2021dynamics-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-feng2021dynamics-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-feng2021dynamics-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-flesch2018comparing-exp1/README.md b/tasks/psychology/psych101-flesch2018comparing-exp1/README.md index ae6c1b93c8ea06c7f25f09f5fc92dbfb596756b6..73fbf79a0be2931e54f880f67b97d841a91a6281 100644 --- a/tasks/psychology/psych101-flesch2018comparing-exp1/README.md +++ b/tasks/psychology/psych101-flesch2018comparing-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Tree-Category Learning Across Gardens -[Task catalog](../../../README.md) +Participants accept or reject trees that vary in leaves and branches across two gardens, with feedback during training. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for flesch2018comparing/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-flesch2018comparing-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `flesch2018comparing/exp1.csv` | +| Public data | 256 train and 64 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-flesch2018comparing-exp1/public) contains 2 files (31,867,420 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-flesch2018comparing-exp1/public) contains 2 files (31,867,420 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-flesch2018comparing-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-flesch2018comparing-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-flesch2018comparing-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-flesch2018comparing-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-frey2017cct-exp1/README.md b/tasks/psychology/psych101-frey2017cct-exp1/README.md index 57cde2dd701fd4fd9a8112450ff444efb0672cff..4b1caa035678d33c23a55eb049d22c99e6c603de 100644 --- a/tasks/psychology/psych101-frey2017cct-exp1/README.md +++ b/tasks/psychology/psych101-frey2017cct-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Stop-or-Continue Card Choices -[Task catalog](../../../README.md) +Participants turn over gain or loss cards and can stop a round to claim its current payout. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for frey2017cct/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-frey2017cct-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `frey2017cct/exp1.csv` | +| Public data | 1094 train and 274 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-frey2017cct-exp1/public) contains 2 files (71,600,868 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-frey2017cct-exp1/public) contains 2 files (71,600,868 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-frey2017cct-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-frey2017cct-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-frey2017cct-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-frey2017cct-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-frey2017risk-exp1/README.md b/tasks/psychology/psych101-frey2017risk-exp1/README.md index c865ab6df7176eea35bc948edf5222a072a7be99..25f748d8bd55d104816d0cddb98d95fbe51675b2 100644 --- a/tasks/psychology/psych101-frey2017risk-exp1/README.md +++ b/tasks/psychology/psych101-frey2017risk-exp1/README.md @@ -1,32 +1,28 @@ # Predicting Human Balloon Pumping and Stopping -[Task catalog](../../../README.md) +Participants pump a balloon for points or stop to collect the accumulated points. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for frey2017risk/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-frey2017risk-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `frey2017risk/exp1.csv` | +| Public data | 1064 train and 267 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-frey2017risk-exp1/public) contains 2 files (12,928,138 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-frey2017risk-exp1/public) contains 2 files (12,928,138 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-frey2017risk-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-frey2017risk-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-frey2017risk-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-frey2017risk-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-garcia2023experiential-exp1/README.md b/tasks/psychology/psych101-garcia2023experiential-exp1/README.md index aaf1a20a446d0aaf39c26b5f2605fc69262c472a..6143db1e60cc377e762b09c02fae0124fbf7f1ee 100644 --- a/tasks/psychology/psych101-garcia2023experiential-exp1/README.md +++ b/tasks/psychology/psych101-garcia2023experiential-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Reward Choices and Odds Estimates — Experiment 1 -[Task catalog](../../../README.md) +Participants choose between reward options across three phases and later estimate each option's chance of winning. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for garcia2023experiential/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-garcia2023experiential-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `garcia2023experiential/exp1.csv` | +| Public data | 69 train and 18 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-garcia2023experiential-exp1/public) contains 2 files (2,951,357 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-garcia2023experiential-exp1/public) contains 2 files (2,951,357 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-garcia2023experiential-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-garcia2023experiential-exp2/README.md b/tasks/psychology/psych101-garcia2023experiential-exp2/README.md index 315241c94e914aa3fd5bed78903469a164e9958e..404283f7b5e8c72ff2512c6f28413ad2fd53e8c0 100644 --- a/tasks/psychology/psych101-garcia2023experiential-exp2/README.md +++ b/tasks/psychology/psych101-garcia2023experiential-exp2/README.md @@ -1,32 +1,28 @@ # Modeling Human Reward Choices and Odds Estimates — Experiment 2 -[Task catalog](../../../README.md) +Participants choose between reward options across three phases and later estimate each option's chance of winning. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for garcia2023experiential/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-garcia2023experiential-exp2` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `garcia2023experiential/exp2.csv` | +| Public data | 69 train and 18 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-garcia2023experiential-exp2/public) contains 2 files (2,951,505 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-garcia2023experiential-exp2/public) contains 2 files (2,951,505 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp2/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-garcia2023experiential-exp2/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-garcia2023experiential-exp3/README.md b/tasks/psychology/psych101-garcia2023experiential-exp3/README.md index 95175d07cffaecd1813ae09bcacce17db274b211..d0deefaa764e8aa5c8650339e443086ac793547b 100644 --- a/tasks/psychology/psych101-garcia2023experiential-exp3/README.md +++ b/tasks/psychology/psych101-garcia2023experiential-exp3/README.md @@ -1,32 +1,28 @@ # Modeling Human Reward Choices and Odds Estimates — Experiment 3 -[Task catalog](../../../README.md) +Participants choose between reward options across three phases and later estimate each option's chance of winning. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for garcia2023experiential/exp3.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-garcia2023experiential-exp3` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `garcia2023experiential/exp3.csv` | +| Public data | 68 train and 18 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-garcia2023experiential-exp3/public) contains 2 files (2,917,546 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-garcia2023experiential-exp3/public) contains 2 files (2,917,546 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp3/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp3/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-garcia2023experiential-exp3/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp3/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-garcia2023experiential-exp4/README.md b/tasks/psychology/psych101-garcia2023experiential-exp4/README.md index 7da31e6bb3087df1a853279b8c7423dd9224cb47..003d9c39f8e861797a0efa1ce2a1f7582d1b5d6b 100644 --- a/tasks/psychology/psych101-garcia2023experiential-exp4/README.md +++ b/tasks/psychology/psych101-garcia2023experiential-exp4/README.md @@ -1,32 +1,28 @@ # Modeling Human Reward Choices and Odds Estimates — Experiment 4 -[Task catalog](../../../README.md) +Participants choose between reward options across three phases and later estimate each option's chance of winning. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for garcia2023experiential/exp4.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-garcia2023experiential-exp4` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `garcia2023experiential/exp4.csv` | +| Public data | 68 train and 18 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-garcia2023experiential-exp4/public) contains 2 files (2,292,628 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-garcia2023experiential-exp4/public) contains 2 files (2,292,628 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp4/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp4/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-garcia2023experiential-exp4/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-garcia2023experiential-exp4/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-gershman2018deconstructing-exp1/README.md b/tasks/psychology/psych101-gershman2018deconstructing-exp1/README.md index feffefab52c89011a8005832a698654835852512..d9ba592e745795ebe24bdaaae9649bf1a4079548 100644 --- a/tasks/psychology/psych101-gershman2018deconstructing-exp1/README.md +++ b/tasks/psychology/psych101-gershman2018deconstructing-exp1/README.md @@ -1,32 +1,28 @@ # Human Choices Against a Fixed-Zero Slot Machine -[Task catalog](../../../README.md) +Participants choose between a variable slot machine and one that always gives zero points. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of gershman2018deconstructing/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-gershman2018deconstructing-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `gershman2018deconstructing/exp1.csv` | +| Public data | 32 train and 8 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `gershman_two_machine_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-gershman2018deconstructing-exp1/public) contains 2 files (319,085 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-gershman2018deconstructing-exp1/public) contains 2 files (319,085 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2018deconstructing-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2018deconstructing-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-gershman2018deconstructing-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2018deconstructing-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-gershman2018deconstructing-exp2/README.md b/tasks/psychology/psych101-gershman2018deconstructing-exp2/README.md index a46e96fb5d6af454328e47ec740d6e808f8112e4..53f4ca8615e992fcb815868e377ca1b74d36fada 100644 --- a/tasks/psychology/psych101-gershman2018deconstructing-exp2/README.md +++ b/tasks/psychology/psych101-gershman2018deconstructing-exp2/README.md @@ -1,32 +1,28 @@ # Human Choices Between Unequal Slot Machines -[Task catalog](../../../README.md) +Participants repeatedly choose between two variable slot machines, one of which is better on average. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of gershman2018deconstructing/exp2.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-gershman2018deconstructing-exp2` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `gershman2018deconstructing/exp2.csv` | +| Public data | 32 train and 8 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `gershman_two_machine_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-gershman2018deconstructing-exp2/public) contains 2 files (321,792 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-gershman2018deconstructing-exp2/public) contains 2 files (321,792 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2018deconstructing-exp2/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2018deconstructing-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-gershman2018deconstructing-exp2/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2018deconstructing-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-gershman2020reward-exp1/README.md b/tasks/psychology/psych101-gershman2020reward-exp1/README.md index 67e188c6f9544ea544fe62e8ec58478f76e4da0c..d0d0dcf875ae32bdc6b60c3ae0d2f2487c810f98 100644 --- a/tasks/psychology/psych101-gershman2020reward-exp1/README.md +++ b/tasks/psychology/psych101-gershman2020reward-exp1/README.md @@ -1,32 +1,28 @@ # Human Stimulus–Response Learning from Rewards -[Task catalog](../../../README.md) +Participants learn which of three keys earns a reward for each presented stimulus. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for gershman2020reward/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-gershman2020reward-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `gershman2020reward/exp1.csv` | +| Public data | 59 train and 15 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-gershman2020reward-exp1/public) contains 2 files (2,322,153 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-gershman2020reward-exp1/public) contains 2 files (2,322,153 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2020reward-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2020reward-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-gershman2020reward-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-gershman2020reward-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-hebart2023things-exp1/README.md b/tasks/psychology/psych101-hebart2023things-exp1/README.md index 3725cbef8110bf3944265e28115fcb91aae0e0d4..97006a8d4950c1c0ff279847303751620a6f7ffc 100644 --- a/tasks/psychology/psych101-hebart2023things-exp1/README.md +++ b/tasks/psychology/psych101-hebart2023things-exp1/README.md @@ -1,32 +1,28 @@ # Predicting Human Odd-One-Out Judgments -[Task catalog](../../../README.md) +Participants select the least similar object from each three-object group. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for hebart2023things/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-hebart2023things-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `hebart2023things/exp1.csv` | +| Public data | 8897 train and 2225 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-hebart2023things-exp1/public) contains 2 files (156,881,709 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-hebart2023things-exp1/public) contains 2 files (156,881,709 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-hebart2023things-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-hebart2023things-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-hebart2023things-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-hebart2023things-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-hilbig2014generalized-exp1/README.md b/tasks/psychology/psych101-hilbig2014generalized-exp1/README.md index e9e8d213287a56b302a051d124ced8d9fdb454cc..1a0c7b07e979b7ba158c7e7357a34c6f459ebb5c 100644 --- a/tasks/psychology/psych101-hilbig2014generalized-exp1/README.md +++ b/tasks/psychology/psych101-hilbig2014generalized-exp1/README.md @@ -1,32 +1,28 @@ # Human Product Choices from Expert Ratings -[Task catalog](../../../README.md) +Participants compare two fictional products using four expert ratings and choose one product. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of hilbig2014generalized/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-hilbig2014generalized-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `hilbig2014generalized/exp1.csv` | +| Public data | 58 train and 15 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `hilbig_two_product_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-hilbig2014generalized-exp1/public) contains 2 files (591,437 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-hilbig2014generalized-exp1/public) contains 2 files (591,437 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-hilbig2014generalized-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-hilbig2014generalized-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-hilbig2014generalized-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-hilbig2014generalized-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-jansen2021dunningkruger-exp1/README.md b/tasks/psychology/psych101-jansen2021dunningkruger-exp1/README.md index a5b7dd9afa5d3feb340257c2a543c416a49ba9e4..823a539bef0488a66935bdabbce1a5a184fa4802 100644 --- a/tasks/psychology/psych101-jansen2021dunningkruger-exp1/README.md +++ b/tasks/psychology/psych101-jansen2021dunningkruger-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Grammar Quiz Self-Estimates -[Task catalog](../../../README.md) +Participants estimate how many questions they will answer correctly on a 20-question grammar quiz. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for jansen2021dunningkruger/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-jansen2021dunningkruger-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `jansen2021dunningkruger/exp1.csv` | +| Public data | 2553 train and 639 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-jansen2021dunningkruger-exp1/public) contains 2 files (31,736,579 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-jansen2021dunningkruger-exp1/public) contains 2 files (31,736,579 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-jansen2021dunningkruger-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-jansen2021dunningkruger-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-jansen2021dunningkruger-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-jansen2021dunningkruger-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-kool2016when-exp1/README.md b/tasks/psychology/psych101-kool2016when-exp1/README.md index 071d507363b4558edb465a027a7aa322d025714e..b6798f37a2e8287b56ef4de8d035baa9bbcef551 100644 --- a/tasks/psychology/psych101-kool2016when-exp1/README.md +++ b/tasks/psychology/psych101-kool2016when-exp1/README.md @@ -1,32 +1,28 @@ # Predicting Human Spaceship Choices amid Treasure and Antimatter -[Task catalog](../../../README.md) +Participants choose spaceships to collect treasure while avoiding antimatter from changing alien mines. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for kool2016when/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-kool2016when-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `kool2016when/exp1.csv` | +| Public data | 143 train and 36 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-kool2016when-exp1/public) contains 2 files (2,813,931 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-kool2016when-exp1/public) contains 2 files (2,813,931 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2016when-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2016when-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-kool2016when-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2016when-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-kool2016when-exp2/README.md b/tasks/psychology/psych101-kool2016when-exp2/README.md index 2423b2d179c11e731d16235bdc493b37dd8f1a89..0b76d8cf88daabe49a8c6573ba2512e7aa2f6e26 100644 --- a/tasks/psychology/psych101-kool2016when-exp2/README.md +++ b/tasks/psychology/psych101-kool2016when-exp2/README.md @@ -1,32 +1,28 @@ # Predicting Human Spaceship and Alien Choices for Treasure -[Task catalog](../../../README.md) +Participants choose spaceships and alien mines to collect treasure as mine rewards change. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for kool2016when/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-kool2016when-exp2` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `kool2016when/exp2.csv` | +| Public data | 150 train and 38 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-kool2016when-exp2/public) contains 2 files (4,096,825 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-kool2016when-exp2/public) contains 2 files (4,096,825 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2016when-exp2/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2016when-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-kool2016when-exp2/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2016when-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-kool2017cost-exp1/README.md b/tasks/psychology/psych101-kool2017cost-exp1/README.md index e78fc44420fb82b57e334ea43388c3ae5025010a..ee45cc5958b8c204cad371dc095fabc7dc423902 100644 --- a/tasks/psychology/psych101-kool2017cost-exp1/README.md +++ b/tasks/psychology/psych101-kool2017cost-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Spaceship Choices with Treasure Multipliers -[Task catalog](../../../README.md) +Participants choose spaceships for changing treasure rewards after learning whether a reward multiplier applies. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for kool2017cost/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-kool2017cost-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `kool2017cost/exp1.csv` | +| Public data | 74 train and 19 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-kool2017cost-exp1/public) contains 2 files (3,703,289 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-kool2017cost-exp1/public) contains 2 files (3,703,289 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2017cost-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2017cost-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-kool2017cost-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2017cost-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-kool2017cost-exp2/README.md b/tasks/psychology/psych101-kool2017cost-exp2/README.md index 461b8d950f729672df2cc859cc0c8424662eb2de..60d617034c39127e27f71f2cde04191cae487bde 100644 --- a/tasks/psychology/psych101-kool2017cost-exp2/README.md +++ b/tasks/psychology/psych101-kool2017cost-exp2/README.md @@ -1,32 +1,28 @@ # Modeling Human Spaceship and Alien Choices with Multipliers -[Task catalog](../../../README.md) +Participants choose spaceships and alien mines for treasure after learning whether a reward multiplier applies. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for kool2017cost/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-kool2017cost-exp2` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `kool2017cost/exp2.csv` | +| Public data | 70 train and 18 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-kool2017cost-exp2/public) contains 2 files (3,618,680 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-kool2017cost-exp2/public) contains 2 files (3,618,680 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2017cost-exp2/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2017cost-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-kool2017cost-exp2/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kool2017cost-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-krueger2022identifying-exp1/README.md b/tasks/psychology/psych101-krueger2022identifying-exp1/README.md index 0c976e1609846aceb7460090cf9325d37ee584de..5fd4fb199e1410f1c39d737f2566f4db0a0aefae 100644 --- a/tasks/psychology/psych101-krueger2022identifying-exp1/README.md +++ b/tasks/psychology/psych101-krueger2022identifying-exp1/README.md @@ -1,32 +1,28 @@ # Human Choices Among Six Gambles -[Task catalog](../../../README.md) +Participants choose one of six gambles, then receive a payoff linked to the chosen gamble and a drawn ball color. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for krueger2022identifying/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-krueger2022identifying-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `krueger2022identifying/exp1.csv` | +| Public data | 1404 train and 351 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-krueger2022identifying-exp1/public) contains 2 files (28,635,461 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-krueger2022identifying-exp1/public) contains 2 files (28,635,461 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-krueger2022identifying-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-krueger2022identifying-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-krueger2022identifying-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-krueger2022identifying-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-kumar2023disentangling-exp1/README.md b/tasks/psychology/psych101-kumar2023disentangling-exp1/README.md index 8e335f669f7ab0a9a547ce35d832f4c7c7188507..a247c4dd086c91e0b5d53390920772aa42a5fedb 100644 --- a/tasks/psychology/psych101-kumar2023disentangling-exp1/README.md +++ b/tasks/psychology/psych101-kumar2023disentangling-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Choices on a Hidden Binary Grid -[Task catalog](../../../README.md) +Participants select unrevealed locations on a 7×7 grid and try to reveal ones while avoiding zeros. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for kumar2023disentangling/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-kumar2023disentangling-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `kumar2023disentangling/exp1.csv` | +| Public data | 565 train and 142 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-kumar2023disentangling-exp1/public) contains 2 files (42,562,418 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-kumar2023disentangling-exp1/public) contains 2 files (42,562,418 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kumar2023disentangling-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kumar2023disentangling-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-kumar2023disentangling-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-kumar2023disentangling-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md b/tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md index 30e63e8a9b0080d0b2de7994ff354d3bbf1edbbc..22d1b4db22ab944c817825d87c18f6ebb10116e0 100644 --- a/tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md +++ b/tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Choice in a Casino Task -[Task catalog](../../../README.md) +Participants visit four casinos and choose between two slot machines to collect stochastic rewards. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of lefebvre2017behavioural/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-lefebvre2017behavioural-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `lefebvre2017behavioural/exp1.csv` | +| Public data | 35 train and 9 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `casino_two_machine_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-lefebvre2017behavioural-exp1/public) contains 2 files (450,595 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-lefebvre2017behavioural-exp1/public) contains 2 files (450,595 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-lefebvre2017behavioural-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-lefebvre2017behavioural-exp2/README.md b/tasks/psychology/psych101-lefebvre2017behavioural-exp2/README.md index 8a8f7980ef3c13acf1d819ed9d47bb15edef57a9..7fc88fb769bc294401e3e8a71596f79412bf608a 100644 --- a/tasks/psychology/psych101-lefebvre2017behavioural-exp2/README.md +++ b/tasks/psychology/psych101-lefebvre2017behavioural-exp2/README.md @@ -1,32 +1,28 @@ # Modeling Human Casino Choices with Gains and Losses -[Task catalog](../../../README.md) +Participants visit four casinos and choose between two machines that can return positive or negative points. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of lefebvre2017behavioural/exp2.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-lefebvre2017behavioural-exp2` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `lefebvre2017behavioural/exp2.csv` | +| Public data | 26 train and 7 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `casino_two_machine_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-lefebvre2017behavioural-exp2/public) contains 2 files (339,457 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-lefebvre2017behavioural-exp2/public) contains 2 files (339,457 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-lefebvre2017behavioural-exp2/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-lefebvre2017behavioural-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-lefebvre2017behavioural-exp2/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-lefebvre2017behavioural-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-levering2020revisiting-exp1/README.md b/tasks/psychology/psych101-levering2020revisiting-exp1/README.md index 42da08835d3b96964f4775af5a94f5486c7f8638..e0829abb92fb9aa2813a912779190f8fdbe90052 100644 --- a/tasks/psychology/psych101-levering2020revisiting-exp1/README.md +++ b/tasks/psychology/psych101-levering2020revisiting-exp1/README.md @@ -1,32 +1,28 @@ # Human Object Classification and Typicality Ratings — Experiment 1 -[Task catalog](../../../README.md) +Participants classify objects by shape, size, and shading, then rate category typicality in a test block. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for levering2020revisiting/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-levering2020revisiting-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `levering2020revisiting/exp1.csv` | +| Public data | 100 train and 26 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-levering2020revisiting-exp1/public) contains 2 files (1,229,159 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-levering2020revisiting-exp1/public) contains 2 files (1,229,159 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-levering2020revisiting-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-levering2020revisiting-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-levering2020revisiting-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-levering2020revisiting-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-levering2020revisiting-exp2/README.md b/tasks/psychology/psych101-levering2020revisiting-exp2/README.md index 5feaedea8c3e615f45cfa7aa34d1000796a57444..89cca6c47980f18b2b36f806ed57ec691e339924 100644 --- a/tasks/psychology/psych101-levering2020revisiting-exp2/README.md +++ b/tasks/psychology/psych101-levering2020revisiting-exp2/README.md @@ -1,32 +1,28 @@ # Human Object Classification and Typicality Ratings — Experiment 2 -[Task catalog](../../../README.md) +Participants classify objects by shape, size, and shading, then rate category typicality in a test block. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for levering2020revisiting/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-levering2020revisiting-exp2` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `levering2020revisiting/exp2.csv` | +| Public data | 81 train and 21 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-levering2020revisiting-exp2/public) contains 2 files (995,024 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-levering2020revisiting-exp2/public) contains 2 files (995,024 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-levering2020revisiting-exp2/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-levering2020revisiting-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-levering2020revisiting-exp2/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-levering2020revisiting-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-ludwig2023human-exp0/README.md b/tasks/psychology/psych101-ludwig2023human-exp0/README.md index 70732bf3e8905c48eddcbae8cfca6009523a0119..b6f754c91f90cb3c7561c10240340fe1ce07e880 100644 --- a/tasks/psychology/psych101-ludwig2023human-exp0/README.md +++ b/tasks/psychology/psych101-ludwig2023human-exp0/README.md @@ -1,32 +1,28 @@ # Modeling Human Fruit-Market Navigation and Feeding — Experiment 0 -[Task catalog](../../../README.md) +Participants move through a fruit market, collect fruits with two vitamins, and feed animals with different preferences. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of ludwig2023human/exp0.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-ludwig2023human-exp0` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `ludwig2023human/exp0.csv` | +| Public data | 47 train and 12 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `ludwig_left_right_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-ludwig2023human-exp0/public) contains 2 files (2,623,321 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-ludwig2023human-exp0/public) contains 2 files (2,623,321 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp0/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp0/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-ludwig2023human-exp0/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp0/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-ludwig2023human-exp1/README.md b/tasks/psychology/psych101-ludwig2023human-exp1/README.md index a194c576c47d846f64dddc4df7ee92d4db2f628e..42e6fceaab01d1940975d95996faea3a32234d0b 100644 --- a/tasks/psychology/psych101-ludwig2023human-exp1/README.md +++ b/tasks/psychology/psych101-ludwig2023human-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Fruit-Market Navigation and Feeding — Experiment 1 -[Task catalog](../../../README.md) +Participants move through a fruit market, collect fruits with two vitamins, and feed animals with different preferences. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of ludwig2023human/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-ludwig2023human-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `ludwig2023human/exp1.csv` | +| Public data | 15 train and 4 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `ludwig_left_right_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-ludwig2023human-exp1/public) contains 2 files (847,355 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-ludwig2023human-exp1/public) contains 2 files (847,355 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-ludwig2023human-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-ludwig2023human-exp2/README.md b/tasks/psychology/psych101-ludwig2023human-exp2/README.md index 112b5e8c7b224d41f48f369b86fc696775c3fe12..dcb99a253953c541260c6d80bda939929987182b 100644 --- a/tasks/psychology/psych101-ludwig2023human-exp2/README.md +++ b/tasks/psychology/psych101-ludwig2023human-exp2/README.md @@ -1,32 +1,28 @@ # Modeling Human Fruit-Market Navigation and Feeding — Experiment 2 -[Task catalog](../../../README.md) +Participants move through a fruit market, collect fruits with two vitamins, and feed animals with different preferences. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of ludwig2023human/exp2.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-ludwig2023human-exp2` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `ludwig2023human/exp2.csv` | +| Public data | 14 train and 4 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `ludwig_left_right_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-ludwig2023human-exp2/public) contains 2 files (799,996 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-ludwig2023human-exp2/public) contains 2 files (799,996 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp2/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-ludwig2023human-exp2/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ludwig2023human-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-peterson2021using-exp1/README.md b/tasks/psychology/psych101-peterson2021using-exp1/README.md index ab9090ec2eb530bea905de746c16b74e038f0d57..70b2255f987164350e2b694cde3f8660d2a2fd8f 100644 --- a/tasks/psychology/psych101-peterson2021using-exp1/README.md +++ b/tasks/psychology/psych101-peterson2021using-exp1/README.md @@ -1,32 +1,28 @@ # Human Gamble Choices under Varying Feedback -[Task catalog](../../../README.md) +Participants choose between two gambles while some problems show obtained and missed outcomes and others suppress that feedback. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for peterson2021using/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-peterson2021using-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `peterson2021using/exp1.csv` | +| Public data | 10988 train and 2747 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-peterson2021using-exp1/public) contains 2 files (185,996,551 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-peterson2021using-exp1/public) contains 2 files (185,996,551 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-peterson2021using-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-peterson2021using-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-peterson2021using-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-peterson2021using-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-plonsky2018when-exp1/README.md b/tasks/psychology/psych101-plonsky2018when-exp1/README.md index b8983a02e67063d92056e6dc8a9fc6ca4eeb7973..ee199be06bd73281bb438ad16855e69c8f0ba0a6 100644 --- a/tasks/psychology/psych101-plonsky2018when-exp1/README.md +++ b/tasks/psychology/psych101-plonsky2018when-exp1/README.md @@ -1,32 +1,28 @@ # Human Gamble Choices before and after Feedback -[Task catalog](../../../README.md) +Participants choose between two gambles over repeated encounters, first without feedback and then with both outcomes shown. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for plonsky2018when/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-plonsky2018when-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `plonsky2018when/exp1.csv` | +| Public data | 172 train and 44 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-plonsky2018when-exp1/public) contains 2 files (14,186,060 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-plonsky2018when-exp1/public) contains 2 files (14,186,060 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-plonsky2018when-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-plonsky2018when-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-plonsky2018when-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-plonsky2018when-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-popov2023intent-exp1/README.md b/tasks/psychology/psych101-popov2023intent-exp1/README.md index 133f3a899ca04f86822462146e0c5f633b6c447f..36ce7df0a5231dcd9695a0fc0467856dd1da00e1 100644 --- a/tasks/psychology/psych101-popov2023intent-exp1/README.md +++ b/tasks/psychology/psych101-popov2023intent-exp1/README.md @@ -1,32 +1,28 @@ # Predicting Human Word Study and Recall — Experiment 1 -[Task catalog](../../../README.md) +Participants judge word meanings, solve arithmetic problems, and later recall marked words from study lists. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for popov2023intent/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-popov2023intent-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `popov2023intent/exp1.csv` | +| Public data | 34 train and 9 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-popov2023intent-exp1/public) contains 2 files (897,131 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-popov2023intent-exp1/public) contains 2 files (897,131 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-popov2023intent-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-popov2023intent-exp2/README.md b/tasks/psychology/psych101-popov2023intent-exp2/README.md index edeb5873d1680761900ed6012922657c96ec7730..a0c44e28941b7250e29c3dbd3aea9f2729d766fd 100644 --- a/tasks/psychology/psych101-popov2023intent-exp2/README.md +++ b/tasks/psychology/psych101-popov2023intent-exp2/README.md @@ -1,32 +1,28 @@ # Predicting Human Word-Pair Study and Recall -[Task catalog](../../../README.md) +Participants judge paired word meanings, solve arithmetic problems, and later recall marked word pairs. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for popov2023intent/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-popov2023intent-exp2` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `popov2023intent/exp2.csv` | +| Public data | 33 train and 9 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-popov2023intent-exp2/public) contains 2 files (722,615 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-popov2023intent-exp2/public) contains 2 files (722,615 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp2/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-popov2023intent-exp2/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-popov2023intent-exp3/README.md b/tasks/psychology/psych101-popov2023intent-exp3/README.md index 1ae33c5af0292f8e553151894c6e952acca17e4f..7a6272e58ff2d6fd624a099f2327101a93178838 100644 --- a/tasks/psychology/psych101-popov2023intent-exp3/README.md +++ b/tasks/psychology/psych101-popov2023intent-exp3/README.md @@ -1,32 +1,28 @@ # Predicting Human Word Study and Recall — Experiment 3 -[Task catalog](../../../README.md) +Participants judge word meanings, solve arithmetic problems, and later recall marked words from study lists. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for popov2023intent/exp3.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-popov2023intent-exp3` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `popov2023intent/exp3.csv` | +| Public data | 37 train and 10 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-popov2023intent-exp3/public) contains 2 files (1,081,021 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-popov2023intent-exp3/public) contains 2 files (1,081,021 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp3/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp3/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-popov2023intent-exp3/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-popov2023intent-exp3/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-ruggeri2022globalizability-exp1/README.md b/tasks/psychology/psych101-ruggeri2022globalizability-exp1/README.md index da5708fe845ff713ced636ef72291af992579324..a566f0c11e4842b2feb779a7a3c5ef43aa708244 100644 --- a/tasks/psychology/psych101-ruggeri2022globalizability-exp1/README.md +++ b/tasks/psychology/psych101-ruggeri2022globalizability-exp1/README.md @@ -1,32 +1,28 @@ # Human Preferences for Immediate and Delayed Payments -[Task catalog](../../../README.md) +Participants state preferences between a payment now and a larger payment after a delay. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for ruggeri2022globalizability/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-ruggeri2022globalizability-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `ruggeri2022globalizability/exp1.csv` | +| Public data | 9549 train and 2388 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-ruggeri2022globalizability-exp1/public) contains 2 files (20,495,426 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-ruggeri2022globalizability-exp1/public) contains 2 files (20,495,426 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ruggeri2022globalizability-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ruggeri2022globalizability-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-ruggeri2022globalizability-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-ruggeri2022globalizability-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/README.md b/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/README.md index ae81c17ae5f820ea9ec304a5b13bb4c4ec9de436..24c5f5bb62a0552a747fec1dc64b194e66d606d5 100644 --- a/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/README.md +++ b/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/README.md @@ -1,32 +1,28 @@ # Human Slot-Machine Choices Across Games -[Task catalog](../../../README.md) +Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for sadeghiyeh2020temporal/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-sadeghiyeh2020temporal-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `sadeghiyeh2020temporal/exp1.csv` | +| Public data | 62 train and 16 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/public) contains 2 files (2,735,477 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/public) contains 2 files (2,735,477 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-sadeghiyeh2020temporal-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-schulz2020finding-exp1/README.md b/tasks/psychology/psych101-schulz2020finding-exp1/README.md index d88beba5c43f38d8d63230168031a5adb367b8e2..c8ab47fc7d0e17b455c63f86277680711ae741dd 100644 --- a/tasks/psychology/psych101-schulz2020finding-exp1/README.md +++ b/tasks/psychology/psych101-schulz2020finding-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Search Among Eight Reward Options — Experiment 1 -[Task catalog](../../../README.md) +Participants choose among eight reward options over repeated rounds and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of schulz2020finding/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-schulz2020finding-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `schulz2020finding/exp1.csv` | +| Public data | 88 train and 22 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `schulz_eight_option_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-schulz2020finding-exp1/public) contains 2 files (1,693,724 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-schulz2020finding-exp1/public) contains 2 files (1,693,724 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-schulz2020finding-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-schulz2020finding-exp2/README.md b/tasks/psychology/psych101-schulz2020finding-exp2/README.md index 5e62767e7ee7c4ee0c08361b0f16ff490929ea7c..22ae82df3d14414c862a5bccb2a178bc30e882aa 100644 --- a/tasks/psychology/psych101-schulz2020finding-exp2/README.md +++ b/tasks/psychology/psych101-schulz2020finding-exp2/README.md @@ -1,32 +1,28 @@ # Modeling Human Search Among Eight Reward Options — Experiment 2 -[Task catalog](../../../README.md) +Participants choose among eight reward options over repeated rounds and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of schulz2020finding/exp2.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-schulz2020finding-exp2` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `schulz2020finding/exp2.csv` | +| Public data | 57 train and 15 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `schulz_eight_option_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-schulz2020finding-exp2/public) contains 2 files (1,108,447 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-schulz2020finding-exp2/public) contains 2 files (1,108,447 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp2/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-schulz2020finding-exp2/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-schulz2020finding-exp3/README.md b/tasks/psychology/psych101-schulz2020finding-exp3/README.md index 64d30c97ec6469bad723f9e85657a57627424f59..c5346c48a18efced1da3782be2171692a1f94ba5 100644 --- a/tasks/psychology/psych101-schulz2020finding-exp3/README.md +++ b/tasks/psychology/psych101-schulz2020finding-exp3/README.md @@ -1,32 +1,28 @@ # Modeling Human Search Among Eight Reward Options — Experiment 3 -[Task catalog](../../../README.md) +Participants choose among eight reward options over repeated rounds and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of schulz2020finding/exp3.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-schulz2020finding-exp3` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `schulz2020finding/exp3.csv` | +| Public data | 89 train and 23 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `schulz_eight_option_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-schulz2020finding-exp3/public) contains 2 files (1,723,768 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-schulz2020finding-exp3/public) contains 2 files (1,723,768 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp3/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp3/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-schulz2020finding-exp3/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp3/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-schulz2020finding-exp4/README.md b/tasks/psychology/psych101-schulz2020finding-exp4/README.md index 6386a8c0adea59bc6f4f5d41748d8cac1d204fee..87a961bcee3adfa700975c153e9b93c6ec89d847 100644 --- a/tasks/psychology/psych101-schulz2020finding-exp4/README.md +++ b/tasks/psychology/psych101-schulz2020finding-exp4/README.md @@ -1,32 +1,28 @@ # Modeling Human Search Among Eight Reward Options — Experiment 4 -[Task catalog](../../../README.md) +Participants choose among eight reward options over repeated rounds and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of schulz2020finding/exp4.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-schulz2020finding-exp4` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `schulz2020finding/exp4.csv` | +| Public data | 79 train and 20 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `schulz_eight_option_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-schulz2020finding-exp4/public) contains 2 files (1,524,152 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-schulz2020finding-exp4/public) contains 2 files (1,524,152 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp4/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp4/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-schulz2020finding-exp4/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp4/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-schulz2020finding-exp5/README.md b/tasks/psychology/psych101-schulz2020finding-exp5/README.md index 380966148d94e62642da87d54e8bacb3454cc63b..1560ef4bcaf385c9e967cb82a4e0be737aa9d2bf 100644 --- a/tasks/psychology/psych101-schulz2020finding-exp5/README.md +++ b/tasks/psychology/psych101-schulz2020finding-exp5/README.md @@ -1,32 +1,28 @@ # Modeling Human Search Among Eight Reward Options — Experiment 5 -[Task catalog](../../../README.md) +Participants choose among eight reward options over repeated rounds and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of schulz2020finding/exp5.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-schulz2020finding-exp5` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `schulz2020finding/exp5.csv` | +| Public data | 112 train and 29 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `schulz_eight_option_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-schulz2020finding-exp5/public) contains 2 files (2,300,511 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-schulz2020finding-exp5/public) contains 2 files (2,300,511 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp5/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp5/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-schulz2020finding-exp5/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-schulz2020finding-exp5/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-somerville2017charting-exp1/README.md b/tasks/psychology/psych101-somerville2017charting-exp1/README.md index 5c924acb10cd4d000508cb9d7a206543ed0b410a..bd5802ceed821c88e1ec278e90efdf97396a2dbb 100644 --- a/tasks/psychology/psych101-somerville2017charting-exp1/README.md +++ b/tasks/psychology/psych101-somerville2017charting-exp1/README.md @@ -1,32 +1,28 @@ # Human Exploration of Two Slot Machines -[Task catalog](../../../README.md) +Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for somerville2017charting/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-somerville2017charting-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `somerville2017charting/exp1.csv` | +| Public data | 62 train and 16 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-somerville2017charting-exp1/public) contains 2 files (4,696,596 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-somerville2017charting-exp1/public) contains 2 files (4,696,596 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-somerville2017charting-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-somerville2017charting-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-somerville2017charting-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-somerville2017charting-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-speekenbrink2008learning-exp1/README.md b/tasks/psychology/psych101-speekenbrink2008learning-exp1/README.md index b34d28d4c9036e45c9b52d47d1e4584d4bd9f1b2..0bde65812f7538c469b7919d88208643aaa73ac9 100644 --- a/tasks/psychology/psych101-speekenbrink2008learning-exp1/README.md +++ b/tasks/psychology/psych101-speekenbrink2008learning-exp1/README.md @@ -1,32 +1,28 @@ # Predicting Human Weather Judgments from Tarot Cards -[Task catalog](../../../README.md) +Participants judge whether combinations of one to three tarot cards predict rainy or fine weather. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of speekenbrink2008learning/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-speekenbrink2008learning-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `speekenbrink2008learning/exp1.csv` | +| Public data | 18 train and 5 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `speekenbrink_weather_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-speekenbrink2008learning-exp1/public) contains 2 files (497,343 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-speekenbrink2008learning-exp1/public) contains 2 files (497,343 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-speekenbrink2008learning-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-speekenbrink2008learning-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-speekenbrink2008learning-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-speekenbrink2008learning-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-steingroever2015data-exp1/README.md b/tasks/psychology/psych101-steingroever2015data-exp1/README.md index 2d66cc6d63e9cd5b6d486bdab73e927bcb2f1ae2..2c7d0a1593eb087f59302769e36343367603cd82 100644 --- a/tasks/psychology/psych101-steingroever2015data-exp1/README.md +++ b/tasks/psychology/psych101-steingroever2015data-exp1/README.md @@ -1,32 +1,28 @@ # Human Choices from Four Card Decks — Experiment 1 -[Task catalog](../../../README.md) +Participants draw cards from four decks and experience varying gains and occasional losses. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of steingroever2015data/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-steingroever2015data-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `steingroever2015data/exp1.csv` | +| Public data | 328 train and 82 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `iowa_four_deck_v0`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-steingroever2015data-exp1/public) contains 2 files (2,193,605 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-steingroever2015data-exp1/public) contains 2 files (2,193,605 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-steingroever2015data-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-steingroever2015data-exp2/README.md b/tasks/psychology/psych101-steingroever2015data-exp2/README.md index 05b6cfcdab5f55c3b3ca2f504554c60e36533a76..8b56fc7e8eeb6985a86944623161df41c94790e1 100644 --- a/tasks/psychology/psych101-steingroever2015data-exp2/README.md +++ b/tasks/psychology/psych101-steingroever2015data-exp2/README.md @@ -1,32 +1,28 @@ # Human Choices from Four Card Decks — Experiment 2 -[Task catalog](../../../README.md) +Participants draw cards from four decks and experience varying gains and occasional losses. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of steingroever2015data/exp2.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-steingroever2015data-exp2` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `steingroever2015data/exp2.csv` | +| Public data | 10 train and 3 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `iowa_four_deck_v0`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-steingroever2015data-exp2/public) contains 2 files (66,396 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-steingroever2015data-exp2/public) contains 2 files (66,396 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp2/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-steingroever2015data-exp2/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-steingroever2015data-exp3/README.md b/tasks/psychology/psych101-steingroever2015data-exp3/README.md index fd991c22e28833e1f6c4141b1ec1c714d42ef262..693e1b7310c130d4306d6f615e217f00ca934b04 100644 --- a/tasks/psychology/psych101-steingroever2015data-exp3/README.md +++ b/tasks/psychology/psych101-steingroever2015data-exp3/README.md @@ -1,32 +1,28 @@ # Human Choices from Four Card Decks — Experiment 3 -[Task catalog](../../../README.md) +Participants draw cards from four decks and experience varying gains and occasional losses. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of steingroever2015data/exp3.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-steingroever2015data-exp3` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `steingroever2015data/exp3.csv` | +| Public data | 70 train and 18 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `iowa_four_deck_v0`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-steingroever2015data-exp3/public) contains 2 files (681,645 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-steingroever2015data-exp3/public) contains 2 files (681,645 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp3/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp3/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-steingroever2015data-exp3/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-steingroever2015data-exp3/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-tomov2020discovery-exp2/README.md b/tasks/psychology/psych101-tomov2020discovery-exp2/README.md index fe8287eb6382e6003169aafe2e777e28a1e25e7b..c585d5b754372b8cd310cdf922de5d92b27b63cb 100644 --- a/tasks/psychology/psych101-tomov2020discovery-exp2/README.md +++ b/tasks/psychology/psych101-tomov2020discovery-exp2/README.md @@ -1,32 +1,28 @@ # Predicting Human Subway Navigation — Experiment 2 -[Task catalog](../../../README.md) +Participants plan routes from a start station to a goal through an unfamiliar subway network. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for tomov2020discovery/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-tomov2020discovery-exp2` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `tomov2020discovery/exp2.csv` | +| Public data | 175 train and 44 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-tomov2020discovery-exp2/public) contains 2 files (12,159,394 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-tomov2020discovery-exp2/public) contains 2 files (12,159,394 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp2/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-tomov2020discovery-exp2/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-tomov2020discovery-exp4/README.md b/tasks/psychology/psych101-tomov2020discovery-exp4/README.md index 3efbc8296b12ee9ae5e42d35658b8e1e863f4e8b..243a18ad37062194191ad42e1832d8052b47a96d 100644 --- a/tasks/psychology/psych101-tomov2020discovery-exp4/README.md +++ b/tasks/psychology/psych101-tomov2020discovery-exp4/README.md @@ -1,32 +1,28 @@ # Predicting Human Subway Navigation — Experiment 4 -[Task catalog](../../../README.md) +Participants plan routes from a start station to a goal through an unfamiliar subway network. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for tomov2020discovery/exp4.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-tomov2020discovery-exp4` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `tomov2020discovery/exp4.csv` | +| Public data | 53 train and 14 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-tomov2020discovery-exp4/public) contains 2 files (3,021,550 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-tomov2020discovery-exp4/public) contains 2 files (3,021,550 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp4/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp4/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-tomov2020discovery-exp4/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp4/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-tomov2020discovery-exp5/README.md b/tasks/psychology/psych101-tomov2020discovery-exp5/README.md index ebc25321a8667ea40528a167bbb212e36a64b6fe..5fe14c8389a74c9650a3fa91f07c4fca4c76d5fc 100644 --- a/tasks/psychology/psych101-tomov2020discovery-exp5/README.md +++ b/tasks/psychology/psych101-tomov2020discovery-exp5/README.md @@ -1,32 +1,28 @@ # Predicting Human Subway Navigation — Experiment 5 -[Task catalog](../../../README.md) +Participants plan routes from a start station to a goal through an unfamiliar subway network. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for tomov2020discovery/exp5.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-tomov2020discovery-exp5` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `tomov2020discovery/exp5.csv` | +| Public data | 276 train and 70 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-tomov2020discovery-exp5/public) contains 2 files (12,369,221 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-tomov2020discovery-exp5/public) contains 2 files (12,369,221 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp5/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp5/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-tomov2020discovery-exp5/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp5/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-tomov2020discovery-exp7/README.md b/tasks/psychology/psych101-tomov2020discovery-exp7/README.md index fbe675ce7cccc6874998fafa1aa682d38666e6aa..b2e61e50f6e0c18dfe0222620cbe7a996395d315 100644 --- a/tasks/psychology/psych101-tomov2020discovery-exp7/README.md +++ b/tasks/psychology/psych101-tomov2020discovery-exp7/README.md @@ -1,32 +1,28 @@ # Predicting Human Subway Navigation — Experiment 7 -[Task catalog](../../../README.md) +Participants plan routes from a start station to a goal through an unfamiliar subway network. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for tomov2020discovery/exp7.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-tomov2020discovery-exp7` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `tomov2020discovery/exp7.csv` | +| Public data | 125 train and 32 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-tomov2020discovery-exp7/public) contains 2 files (8,601,475 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-tomov2020discovery-exp7/public) contains 2 files (8,601,475 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp7/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp7/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-tomov2020discovery-exp7/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2020discovery-exp7/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-tomov2021multitask-exp1/README.md b/tasks/psychology/psych101-tomov2021multitask-exp1/README.md index 0e1f23f0430faac6ee61c77293f869c3499113ff..aaa50aa5ff64a0839ebe6c4c1e831ef36f3d9ee0 100644 --- a/tasks/psychology/psych101-tomov2021multitask-exp1/README.md +++ b/tasks/psychology/psych101-tomov2021multitask-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Castle-Room Exploration — Experiment 1 -[Task catalog](../../../README.md) +Participants choose doors between castle rooms to find wood, stone, and iron resources. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for tomov2021multitask/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-tomov2021multitask-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `tomov2021multitask/exp1.csv` | +| Public data | 156 train and 40 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-tomov2021multitask-exp1/public) contains 2 files (5,475,976 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-tomov2021multitask-exp1/public) contains 2 files (5,475,976 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2021multitask-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2021multitask-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-tomov2021multitask-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2021multitask-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-tomov2021multitask-exp3/README.md b/tasks/psychology/psych101-tomov2021multitask-exp3/README.md index c72aa677ad5c1bcb36dcd0b98bfd05844fd50b90..722b63c5abd0221b13e2b5484cf48656cf535564 100644 --- a/tasks/psychology/psych101-tomov2021multitask-exp3/README.md +++ b/tasks/psychology/psych101-tomov2021multitask-exp3/README.md @@ -1,32 +1,28 @@ # Modeling Human Castle-Room Exploration — Experiment 3 -[Task catalog](../../../README.md) +Participants choose doors between castle rooms to find wood, stone, and iron resources. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for tomov2021multitask/exp3.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-tomov2021multitask-exp3` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `tomov2021multitask/exp3.csv` | +| Public data | 147 train and 37 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-tomov2021multitask-exp3/public) contains 2 files (5,140,495 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-tomov2021multitask-exp3/public) contains 2 files (5,140,495 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2021multitask-exp3/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2021multitask-exp3/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-tomov2021multitask-exp3/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-tomov2021multitask-exp3/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-waltz2020differential-exp1/README.md b/tasks/psychology/psych101-waltz2020differential-exp1/README.md index 07afc7c385de6344234d87d7825ca7b22a35839d..c02181ce4be932609388e743f9fa37c98885f272 100644 --- a/tasks/psychology/psych101-waltz2020differential-exp1/README.md +++ b/tasks/psychology/psych101-waltz2020differential-exp1/README.md @@ -1,32 +1,28 @@ # Human Slot-Machine Choices Across Games -[Task catalog](../../../README.md) +Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for waltz2020differential/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-waltz2020differential-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `waltz2020differential/exp1.csv` | +| Public data | 28 train and 8 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-waltz2020differential-exp1/public) contains 2 files (1,637,351 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-waltz2020differential-exp1/public) contains 2 files (1,637,351 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-waltz2020differential-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-waltz2020differential-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-waltz2020differential-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-waltz2020differential-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-wilson2014humans-exp1/README.md b/tasks/psychology/psych101-wilson2014humans-exp1/README.md index 7efb10054f788d03c8e9ca886b7b8a8e04a7faff..0193f859300a0eb3889b8f2b0c8b2858488ad3b2 100644 --- a/tasks/psychology/psych101-wilson2014humans-exp1/README.md +++ b/tasks/psychology/psych101-wilson2014humans-exp1/README.md @@ -1,32 +1,28 @@ # Human Two-Slot-Machine Choices — Experiment 1 -[Task catalog](../../../README.md) +Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of wilson2014humans/exp1.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-wilson2014humans-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `wilson2014humans/exp1.csv` | +| Public data | 21 train and 6 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `wilson_two_machine_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wilson2014humans-exp1/public) contains 2 files (3,234,483 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wilson2014humans-exp1/public) contains 2 files (3,234,483 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wilson2014humans-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-wilson2014humans-exp2/README.md b/tasks/psychology/psych101-wilson2014humans-exp2/README.md index 602b9db426d39798d7c7f121f52901127128a43d..e7533b3d9d938497b704a405b07c3deb742d687e 100644 --- a/tasks/psychology/psych101-wilson2014humans-exp2/README.md +++ b/tasks/psychology/psych101-wilson2014humans-exp2/README.md @@ -1,32 +1,28 @@ # Human Two-Slot-Machine Choices — Experiment 2 -[Task catalog](../../../README.md) +Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of wilson2014humans/exp2.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-wilson2014humans-exp2` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `wilson2014humans/exp2.csv` | +| Public data | 5 train and 2 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `wilson_two_machine_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wilson2014humans-exp2/public) contains 2 files (421,444 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wilson2014humans-exp2/public) contains 2 files (421,444 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp2/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wilson2014humans-exp2/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-wilson2014humans-exp3/README.md b/tasks/psychology/psych101-wilson2014humans-exp3/README.md index a53ed22a86ca3e44b0f1cc20ead759c7bf9ecf4b..e73dac430fed32ed97926412f437489157d61349 100644 --- a/tasks/psychology/psych101-wilson2014humans-exp3/README.md +++ b/tasks/psychology/psych101-wilson2014humans-exp3/README.md @@ -1,32 +1,28 @@ # Human Two-Slot-Machine Choices — Experiment 3 -[Task catalog](../../../README.md) +Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of wilson2014humans/exp3.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-wilson2014humans-exp3` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `wilson2014humans/exp3.csv` | +| Public data | 54 train and 14 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `wilson_two_machine_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wilson2014humans-exp3/public) contains 2 files (4,093,232 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wilson2014humans-exp3/public) contains 2 files (4,093,232 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp3/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp3/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wilson2014humans-exp3/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp3/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-wilson2014humans-exp4/README.md b/tasks/psychology/psych101-wilson2014humans-exp4/README.md index fb421289c1623ed354c717ea31f6c424c06f181a..760469dbb3581a425000e6540357f02cbd946a84 100644 --- a/tasks/psychology/psych101-wilson2014humans-exp4/README.md +++ b/tasks/psychology/psych101-wilson2014humans-exp4/README.md @@ -1,32 +1,28 @@ # Human Two-Slot-Machine Choices — Experiment 4 -[Task catalog](../../../README.md) +Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of wilson2014humans/exp4.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-wilson2014humans-exp4` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `wilson2014humans/exp4.csv` | +| Public data | 64 train and 16 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `wilson_two_machine_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wilson2014humans-exp4/public) contains 2 files (4,816,535 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wilson2014humans-exp4/public) contains 2 files (4,816,535 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp4/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp4/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wilson2014humans-exp4/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp4/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-wilson2014humans-exp5/README.md b/tasks/psychology/psych101-wilson2014humans-exp5/README.md index ec33fdff09a898bc59902c6575f36d10457af1f0..bbc9d79251574aef91b5998eb4b336fc5b38d2bd 100644 --- a/tasks/psychology/psych101-wilson2014humans-exp5/README.md +++ b/tasks/psychology/psych101-wilson2014humans-exp5/README.md @@ -1,32 +1,28 @@ # Human Two-Slot-Machine Choices — Experiment 5 -[Task catalog](../../../README.md) +Participants choose between two slot machines over multiple games and observe point outcomes. The agent predicts participants' recorded responses from the information available before each response. -Public-data Agent modeling of wilson2014humans/exp5.csv; independent public-valid response-level NLL only. Historical private Test results are not replayed. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-wilson2014humans-exp5` | -| Collection | BrainPilotBench v1 | -| Task version | `0.1-public-validation` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `wilson2014humans/exp5.csv` | +| Public data | 31 train and 8 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `wilson_two_machine_v1`: probabilities over displayed keys | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wilson2014humans-exp5/public) contains 2 files (2,348,077 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wilson2014humans-exp5/public) contains 2 files (2,348,077 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp5/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp5/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wilson2014humans-exp5/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wilson2014humans-exp5/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-wise2019acomputational-exp1/README.md b/tasks/psychology/psych101-wise2019acomputational-exp1/README.md index b94dd4d14902dc40eb93d86f01bc90600da8c9e6..7b47ae469af55d5c66cd9e9ba06be61e33392966 100644 --- a/tasks/psychology/psych101-wise2019acomputational-exp1/README.md +++ b/tasks/psychology/psych101-wise2019acomputational-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Shock-Probability Estimates from Visual Cues -[Task catalog](../../../README.md) +Participants rate the probability of a shock for visual stimuli and then see each outcome. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for wise2019acomputational/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-wise2019acomputational-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `wise2019acomputational/exp1.csv` | +| Public data | 45 train and 12 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wise2019acomputational-exp1/public) contains 2 files (2,780,468 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wise2019acomputational-exp1/public) contains 2 files (2,780,468 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wise2019acomputational-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wise2019acomputational-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wise2019acomputational-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wise2019acomputational-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-wu2018generalisation-exp1/README.md b/tasks/psychology/psych101-wu2018generalisation-exp1/README.md index ce18affd0045e1ce60698849296802ba76b642fc..fc50db71225e8f0af78adb68fc32b5b3c97f6ddd 100644 --- a/tasks/psychology/psych101-wu2018generalisation-exp1/README.md +++ b/tasks/psychology/psych101-wu2018generalisation-exp1/README.md @@ -1,32 +1,28 @@ # Predicting Human Reward Search Along a Number Line -[Task catalog](../../../README.md) +Participants select numbered options across multiple environments and observe their point rewards. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for wu2018generalisation/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-wu2018generalisation-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `wu2018generalisation/exp1.csv` | +| Public data | 62 train and 16 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wu2018generalisation-exp1/public) contains 2 files (610,382 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wu2018generalisation-exp1/public) contains 2 files (610,382 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2018generalisation-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2018generalisation-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wu2018generalisation-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2018generalisation-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-wu2023chunking-exp1/README.md b/tasks/psychology/psych101-wu2023chunking-exp1/README.md index c4d4156106e163c63093e90711b79bf92f4c2b2f..ffc529f2353c1714f70440f5367dcc9369c5d5be 100644 --- a/tasks/psychology/psych101-wu2023chunking-exp1/README.md +++ b/tasks/psychology/psych101-wu2023chunking-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Responses to Keypress Instructions — Experiment 1 -[Task catalog](../../../README.md) +Participants press the instructed key as quickly and accurately as possible. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for wu2023chunking/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-wu2023chunking-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `wu2023chunking/exp1.csv` | +| Public data | 105 train and 27 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wu2023chunking-exp1/public) contains 2 files (10,124,802 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wu2023chunking-exp1/public) contains 2 files (10,124,802 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2023chunking-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2023chunking-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wu2023chunking-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2023chunking-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-wu2023chunking-exp2/README.md b/tasks/psychology/psych101-wu2023chunking-exp2/README.md index f79538ba4ee45f3924e0700cc9f79c34bd37e325..35cc36774fb1e54d6ee9234acb858b3432006010 100644 --- a/tasks/psychology/psych101-wu2023chunking-exp2/README.md +++ b/tasks/psychology/psych101-wu2023chunking-exp2/README.md @@ -1,32 +1,28 @@ # Modeling Human Responses to Keypress Instructions — Experiment 2 -[Task catalog](../../../README.md) +Participants press the instructed key as quickly and accurately as possible. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for wu2023chunking/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-wu2023chunking-exp2` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `wu2023chunking/exp2.csv` | +| Public data | 84 train and 22 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wu2023chunking-exp2/public) contains 2 files (8,120,731 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wu2023chunking-exp2/public) contains 2 files (8,120,731 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2023chunking-exp2/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2023chunking-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wu2023chunking-exp2/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wu2023chunking-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-wulff2018description-exp1/README.md b/tasks/psychology/psych101-wulff2018description-exp1/README.md index 374f91cb2243d9f1ccbc3d3e85d3a53552bbd41a..18372dbacc81b8b5bad349b4ddc250e3fae34f16 100644 --- a/tasks/psychology/psych101-wulff2018description-exp1/README.md +++ b/tasks/psychology/psych101-wulff2018description-exp1/README.md @@ -1,32 +1,28 @@ # Human Choices Between Described Monetary Lotteries -[Task catalog](../../../README.md) +Participants choose between two lotteries with described outcomes and probabilities. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for wulff2018description/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-wulff2018description-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `wulff2018description/exp1.csv` | +| Public data | 1584 train and 397 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wulff2018description-exp1/public) contains 2 files (6,404,480 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wulff2018description-exp1/public) contains 2 files (6,404,480 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wulff2018description-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wulff2018description-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wulff2018description-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wulff2018description-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-wulff2018sampling-exp1/README.md b/tasks/psychology/psych101-wulff2018sampling-exp1/README.md index a6496c781864808f65932dc707baeac9a34931df..10c6345487e79e48ff99a2246c03f40aa3980abb 100644 --- a/tasks/psychology/psych101-wulff2018sampling-exp1/README.md +++ b/tasks/psychology/psych101-wulff2018sampling-exp1/README.md @@ -1,32 +1,28 @@ # Predicting Human Lottery Sampling and Final Choice -[Task catalog](../../../README.md) +Participants sample two lotteries to learn their outcomes and probabilities before making rewarded choices. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for wulff2018sampling/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-wulff2018sampling-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `wulff2018sampling/exp1.csv` | +| Public data | 3153 train and 789 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wulff2018sampling-exp1/public) contains 2 files (46,735,079 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-wulff2018sampling-exp1/public) contains 2 files (46,735,079 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wulff2018sampling-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wulff2018sampling-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-wulff2018sampling-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-wulff2018sampling-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-xiong2023neural-exp1/README.md b/tasks/psychology/psych101-xiong2023neural-exp1/README.md index 1894cd26a7983cc596b3ec623ae04f9d37468f93..c48fd2fbe3c4eb0576e58be9cba98b18e539a5e1 100644 --- a/tasks/psychology/psych101-xiong2023neural-exp1/README.md +++ b/tasks/psychology/psych101-xiong2023neural-exp1/README.md @@ -1,32 +1,28 @@ # Human Choices with Changing Slot-Machine Rewards -[Task catalog](../../../README.md) +Participants choose between two slot machines as their expected point rewards change across trials. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for xiong2023neural/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-xiong2023neural-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `xiong2023neural/exp1.csv` | +| Public data | 24 train and 6 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-xiong2023neural-exp1/public) contains 2 files (5,105,998 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-xiong2023neural-exp1/public) contains 2 files (5,105,998 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-xiong2023neural-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-xiong2023neural-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-xiong2023neural-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-xiong2023neural-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-zhu2020bayesian-exp1/README.md b/tasks/psychology/psych101-zhu2020bayesian-exp1/README.md index 4a986b89b8371926244ab6ac0a9130950fd44ee2..15f8d96d93468364c0d1ef4eb3ebd8d59bb06f5a 100644 --- a/tasks/psychology/psych101-zhu2020bayesian-exp1/README.md +++ b/tasks/psychology/psych101-zhu2020bayesian-exp1/README.md @@ -1,32 +1,28 @@ # Modeling Human Weather-Probability Estimates — Experiment 1 -[Task catalog](../../../README.md) +Participants type estimates for weather-related event probabilities. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for zhu2020bayesian/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-zhu2020bayesian-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `zhu2020bayesian/exp1.csv` | +| Public data | 44 train and 11 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-zhu2020bayesian-exp1/public) contains 2 files (886,928 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-zhu2020bayesian-exp1/public) contains 2 files (886,928 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zhu2020bayesian-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zhu2020bayesian-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-zhu2020bayesian-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zhu2020bayesian-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-zhu2020bayesian-exp2/README.md b/tasks/psychology/psych101-zhu2020bayesian-exp2/README.md index 2fe322e2150d2a8b5bf2972a0ae5338121d5eabf..5f47159f68f0f0766035417214e4ac7cf386895b 100644 --- a/tasks/psychology/psych101-zhu2020bayesian-exp2/README.md +++ b/tasks/psychology/psych101-zhu2020bayesian-exp2/README.md @@ -1,32 +1,28 @@ # Modeling Human Conditional Weather-Probability Estimates -[Task catalog](../../../README.md) +Participants type estimates for conditional probabilities of weather-related events. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for zhu2020bayesian/exp2.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-zhu2020bayesian-exp2` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `zhu2020bayesian/exp2.csv` | +| Public data | 58 train and 15 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-zhu2020bayesian-exp2/public) contains 2 files (1,742,494 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-zhu2020bayesian-exp2/public) contains 2 files (1,742,494 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zhu2020bayesian-exp2/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zhu2020bayesian-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-zhu2020bayesian-exp2/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zhu2020bayesian-exp2/README.md) · [Source attribution](../../../ATTRIBUTION.md) diff --git a/tasks/psychology/psych101-zorowitz2023data-exp1/README.md b/tasks/psychology/psych101-zorowitz2023data-exp1/README.md index 59b7462cd88c61036b3c8cc7488b64d4f482ebed..fab456504d61789f2e2eaffd68e4c3d618314ea1 100644 --- a/tasks/psychology/psych101-zorowitz2023data-exp1/README.md +++ b/tasks/psychology/psych101-zorowitz2023data-exp1/README.md @@ -1,32 +1,28 @@ # Predicting Human Rocket and Alien Choices for Treasure -[Task catalog](../../../README.md) +Participants choose rockets to reach planets, then choose aliens to trade with for treasure. The agent predicts participants' recorded responses from the information available before each response. -Public Psych-101 marked-response UTF-8 byte+EOS likelihood for zorowitz2023data/exp1.csv. New protocol version; not numerically comparable with historical token or categorical scores. +Agent benchmark results are not yet available. -Agent benchmark results are not yet available. Preparation and fixed-reference checks are not Agent results. +## Task at a glance -## Task and data - -| Field | Value | -|---|---| +| Field | Details | +| --- | --- | | Task ID | `psych101-zorowitz2023data-exp1` | -| Collection | BrainPilotBench v1 | -| Task version | `0.2-byte-next-v1` | -| Data category | Psychology | -| Access | `hosted_public` | -| Primary metric | `mean_response_nll` (minimize) | +| Source experiment | `zorowitz2023data/exp1.csv` | +| Public data | 111 train and 28 valid participants | +| Agent output | `report.md` and three `submission/seed-N/` model bundles | +| Prediction protocol | `byte_next_v1`: next UTF-8 byte or EOS for marked responses | +| Public metric | `mean_response_nll` ↓, nats per response · public validation only | -The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-zorowitz2023data-exp1/public) contains 2 files (5,483,507 bytes). -The [manifest](manifest.json) records each relative path, byte count, and SHA-256 digest. -Use the task data lock in the BrainPilotBench source checkout for commit-pinned downloads. -The `main` links on this page are navigation links, not immutable data identifiers. +## Data access -## Protocol and source +The [public folder](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Public/tree/main/tasks/psychology/psych101-zorowitz2023data-exp1/public) contains 2 files (5,483,507 bytes). The [manifest](manifest.json) lists each path, byte count, and SHA-256 digest. + +Original source terms apply. This catalog does not relicense the data. -The [task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zorowitz2023data-exp1/README.md) describes the inputs, outputs, split, environment, and scoring interface. -Scientific task versions remain separate from the collection name and storage layout. +## Protocol and source -[Source reference](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zorowitz2023data-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md) +The [versioned task guide](https://github.com/NeuroAIHub/BrainPilotBench/blob/7306cc0b0e8958cc8f84918b68446310d8dbc662/tasks/psychology/psych101-zorowitz2023data-exp1/README.md) defines the scientific protocol, preparation, and scoring. -Original source terms apply. This catalog does not relicense the data. +[Frozen source record](https://github.com/NeuroAIHub/BrainPilotBench/blob/9d92b6738189d23607478ee1f71bdb6ff567d07b/tasks/psychology/psych101-zorowitz2023data-exp1/README.md) · [Source attribution](../../../ATTRIBUTION.md)