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- .gitattributes +60 -0
- README.md +252 -0
- README_zh.md +240 -0
- docker/classification/automedbench-classification-docker-image-v0.1.0.json +93 -0
- docker/classification/automedbench-classification-docker-image-v0.1.0.tar.gz +3 -0
- docker/classification/automedbench-classification-docker-image-v0.1.0.tar.gz.sha256 +3 -0
- docker/detection/automedbench-detection-docker-image-v0.1.0.json +77 -0
- docker/detection/automedbench-detection-docker-image-v0.1.0.tar.gz +3 -0
- docker/detection/automedbench-detection-docker-image-v0.1.0.tar.gz.sha256 +3 -0
- docker/enhancement/automedbench-enhancement-docker-image-v0.1.0.json +125 -0
- docker/enhancement/automedbench-enhancement-docker-image-v0.1.0.tar.gz +3 -0
- docker/enhancement/automedbench-enhancement-docker-image-v0.1.0.tar.gz.sha256 +3 -0
- docker/report/automedbench-report-docker-image-v0.1.0.json +93 -0
- docker/report/automedbench-report-docker-image-v0.1.0.tar.gz +3 -0
- docker/report/automedbench-report-docker-image-v0.1.0.tar.gz.sha256 +3 -0
- docker/segmentation/automedbench-segmentation-docker-image-v0.1.0.json +237 -0
- docker/segmentation/automedbench-segmentation-docker-image-v0.1.0.tar.gz +3 -0
- docker/segmentation/automedbench-segmentation-docker-image-v0.1.0.tar.gz.sha256 +3 -0
- docker/synthesis/automedbench-synthesis-docker-image-v0.1.0.json +77 -0
- docker/synthesis/automedbench-synthesis-docker-image-v0.1.0.tar.gz +3 -0
- docker/synthesis/automedbench-synthesis-docker-image-v0.1.0.tar.gz.sha256 +3 -0
- docker/vqa/automedbench-vqa-docker-image-v0.1.0.json +157 -0
- docker/vqa/automedbench-vqa-docker-image-v0.1.0.tar.gz +3 -0
- docker/vqa/automedbench-vqa-docker-image-v0.1.0.tar.gz.sha256 +3 -0
- docs/DATA_POLICY.md +44 -0
- docs/EXECUTION_PLAN.md +88 -0
- docs/RELEASE_STATUS.md +141 -0
- manifests/cell_archives.csv +8 -0
- manifests/cell_images.csv +97 -0
- manifests/cell_verification.csv +97 -0
- manifests/data_policy.csv +49 -0
- manifests/dataset_resolution.csv +49 -0
- manifests/dataset_resolution.json +11 -0
- manifests/release_owned_tasks.csv +16 -0
- manifests/runtime_archive.json +41 -0
- manifests/runtime_images.csv +9 -0
- manifests/source_lock.json +44 -0
- manifests/task_matrix.csv +97 -0
- runtime/automedbench-full-runtime-0.1.0.tar.gz +3 -0
- runtime/automedbench-full-runtime-0.1.0.tar.gz.sha256 +3 -0
- runtime/images.lock.json +89 -0
- schemas/task.schema.json +137 -0
- tasks/_package_manifest.json +682 -0
- tasks/classification/braintumor-cls-task.tar.gz +3 -0
- tasks/classification/chest-xray-pneumonia-cls-task.tar.gz +3 -0
- tasks/classification/crc-histology-cls-task.tar.gz +3 -0
- tasks/classification/patchcamelyon-cls-task.tar.gz +3 -0
- tasks/classification/skin-lesion-cls-task.tar.gz +3 -0
- tasks/detection/bccd-det-task.tar.gz +3 -0
- tasks/detection/dentex-det-task.tar.gz +3 -0
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README.md
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| 1 |
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---
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| 2 |
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license: other
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| 3 |
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tags:
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| 4 |
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- medical
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- benchmark
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| 6 |
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- multimodal
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| 7 |
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- agentic
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| 8 |
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---
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| 9 |
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| 10 |
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# AutoMedBench-Full-release
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| 11 |
+
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| 12 |
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[](https://automedbench.github.io/) [](https://huggingface.co/spaces/MitakaKuma/AutoMedBench-Leaderboard) [](https://huggingface.co/spaces/MitakaKuma/AutoMedBench-Full-Leaderboard) [](https://arxiv.org/abs/2606.01961) [](https://github.com/AutoMedBench/AutoMedBench)
|
| 13 |
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| 14 |
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[中文说明](README_zh.md)
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| 15 |
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| 16 |
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AutoMedBench is a workflow-aware benchmark for autonomous medical-AI research
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| 17 |
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agents. It evaluates both the final task artifact and the S1-S5 research
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| 18 |
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workflow: Plan, Setup, Validate, Inference, and Submit.
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| 19 |
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| 20 |
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This Full release packages **48 tasks** across **7 tracks** with Lite and
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| 21 |
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Standard tiers, for **96 task-tier combinations**. Each combination has a
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| 22 |
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pre-built Docker image. Dataset bytes are **not** bundled — users prepare data
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| 23 |
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independently and mount it at runtime.
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| 24 |
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| 25 |
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## How to Submit
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| 26 |
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**Submission email: <jliu718@ucsc.edu>**
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| 28 |
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| 29 |
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Suggested subject: `AutoMedBench submission - <agent/team name>`
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| 30 |
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| 31 |
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| Priority | What to do | Why it matters |
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| 32 |
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| --- | --- | --- |
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| 33 |
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| **Required** | **Run your agent at least 5 repeated times on the benchmark.** Agent runs can vary because of model sampling, tool-use choices, network timing, and dependency setup. Repeated runs provide a more stable estimate of real performance than a single run. |
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| 34 |
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| **Required** | **Zip all output reports and conversation/transcript files into one archive, then email that zip file to <jliu718@ucsc.edu>.** | The full package lets maintainers verify final artifacts, audit the workflow, and check stability across repeated runs. |
|
| 35 |
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| **Recommended** | **Use a coding agent to launch, monitor, and collect runs.** | Benchmark runs are long and may need log inspection, quick fixes, and clean collection of conversation files. |
|
| 36 |
+
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| 37 |
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## Quick Start
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| 38 |
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| 39 |
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```bash
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| 40 |
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# 1. Download a track Docker image (e.g. segmentation)
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| 41 |
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# From this repository: docker/segmentation/automedbench-segmentation-docker-image-v0.1.0.tar.gz
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| 42 |
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| 43 |
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# 2. Load the Docker image
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| 44 |
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docker load -i automedbench-segmentation-docker-image-v0.1.0.tar.gz
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| 45 |
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| 46 |
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# 3. Set up credentials
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| 47 |
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cp env.example .env
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| 48 |
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# edit .env with your API key
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| 49 |
+
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| 50 |
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# 4. Run a task
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| 51 |
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python docker/orchestrator.py \
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| 52 |
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--agent claude-opus-4-6 \
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| 53 |
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--task kidney-seg-task \
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| 54 |
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--tier lite \
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| 55 |
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--n-patients 20
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| 56 |
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```
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| 57 |
+
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| 58 |
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The Docker image contains the benchmark harness and scoring code. Credentials
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| 59 |
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are passed only at runtime through `.env` or shell environment variables.
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| 60 |
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Dataset files must be mounted separately (see [Data Acquisition](#data-acquisition)
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| 61 |
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below).
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| 62 |
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| 63 |
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## Docker Image Packages
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| 64 |
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|
| 65 |
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Prebuilt per-track Docker image packages are stored in this repository:
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| 66 |
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|
| 67 |
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```text
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| 68 |
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docker/classification/automedbench-classification-docker-image-v0.1.0.tar.gz
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| 69 |
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docker/detection/automedbench-detection-docker-image-v0.1.0.tar.gz
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| 70 |
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docker/enhancement/automedbench-enhancement-docker-image-v0.1.0.tar.gz
|
| 71 |
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docker/report/automedbench-report-docker-image-v0.1.0.tar.gz
|
| 72 |
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docker/segmentation/automedbench-segmentation-docker-image-v0.1.0.tar.gz
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| 73 |
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docker/synthesis/automedbench-synthesis-docker-image-v0.1.0.tar.gz
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| 74 |
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docker/vqa/automedbench-vqa-docker-image-v0.1.0.tar.gz
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| 75 |
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```
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| 76 |
+
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| 77 |
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Each archive is ~3.5 GB and contains all Lite + Standard task-tier images for
|
| 78 |
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that track. The shared runtime archive
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| 79 |
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(`runtime/automedbench-full-runtime-0.1.0.tar.gz`, ~4 GB) supplies the common
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| 80 |
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agent runtime and seven track evaluator images.
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| 81 |
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| 82 |
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After downloading, load all images:
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| 83 |
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| 84 |
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```bash
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| 85 |
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docker load -i runtime/automedbench-full-runtime-0.1.0.tar.gz
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| 86 |
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docker load -i docker/segmentation/automedbench-segmentation-docker-image-v0.1.0.tar.gz
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| 87 |
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# ... repeat for other tracks as needed
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| 88 |
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```
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| 89 |
+
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| 90 |
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## Released Tasks (48 tasks, 96 Lite/Standard combinations)
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| 91 |
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| 92 |
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| Track | Tasks | Metric focus |
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| 93 |
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| --- | ---: | --- |
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| 94 |
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| Segmentation | 14 | Dice (organ + lesion) |
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| 95 |
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| Enhancement | 7 | SSIM |
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| 96 |
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| VQA | 9 | Answer accuracy |
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| 97 |
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| Report generation | 5 | Clinical report quality |
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| 98 |
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| Detection | 4 | mAP@0.5 |
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| 99 |
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| Classification | 5 | Label accuracy |
|
| 100 |
+
| Synthesis | 4 | SSIM |
|
| 101 |
+
|
| 102 |
+
## Data Acquisition
|
| 103 |
+
|
| 104 |
+
**Dataset bytes are not included in this release.** Each task references an
|
| 105 |
+
upstream dataset that must be downloaded independently. The table below lists
|
| 106 |
+
every task's data source, download link, license, and access requirements.
|
| 107 |
+
|
| 108 |
+
### Segmentation (14 tasks)
|
| 109 |
+
|
| 110 |
+
| Task ID | Upstream Dataset | Download Link | License | Access | Approx. Size | Status |
|
| 111 |
+
| --- | --- | --- | --- | --- | --- | --- |
|
| 112 |
+
| `kidney-seg-task` | KiTS19 | [kits19.grand-challenge.org](https://kits19.grand-challenge.org/) | CC BY-NC-SA 4.0 | Public | ~200 MB/case | Acquisition ready |
|
| 113 |
+
| `pancreas-seg-task` | PanTS | [github.com/MrGiovanni/PanTS](https://github.com/MrGiovanni/PanTS) | CC BY-NC-ND 4.0 | Public | ~300–346 GB | Acquisition ready |
|
| 114 |
+
| `pancreas-oar-seg-task` | PanTS | [github.com/MrGiovanni/PanTS](https://github.com/MrGiovanni/PanTS) | CC BY-NC-ND 4.0 | Public | ~300–346 GB | Acquisition ready |
|
| 115 |
+
| `liver-seg-task` | MSD Task03 Liver | [medicaldecathlon.com](https://medicaldecathlon.com/) | Provenance conflict | Public | ~28.9 GB | Staged verified |
|
| 116 |
+
| `aeropath-seg-task` | AeroPath | [zenodo.org/records/10069289](https://zenodo.org/records/10069289) | CC BY 4.0 | Public | ~5.04 GB | Acquisition ready |
|
| 117 |
+
| `tsg-multiorgan-seg-task` | TotalSegmentator v2.0.1 | [zenodo.org/records/10047263](https://zenodo.org/records/10047263) | CC BY 4.0 | Public | ~3.24 GB | Staged verified |
|
| 118 |
+
| `colon-seg-task` | MSD Task10 Colon | [medicaldecathlon.com](https://medicaldecathlon.com/) | CC BY-SA 4.0 | Public | ~6.24 GB | Staged verified |
|
| 119 |
+
| `hepaticvessel-seg-task` | MSD Task08 HepaticVessel | [medicaldecathlon.com](https://medicaldecathlon.com/) | CC BY-SA 4.0 | Public | ~9.35 GB | Staged verified |
|
| 120 |
+
| `spleen-seg-task` | MSD Task09 Spleen | [medicaldecathlon.com](https://medicaldecathlon.com/) | CC BY-SA 4.0 | Public | ~1.61 GB | Staged verified |
|
| 121 |
+
| `heart-seg-task` | MSD Task02 Heart | [medicaldecathlon.com](https://medicaldecathlon.com/) | CC BY-SA 4.0 | Public | ~456 MB | Staged verified |
|
| 122 |
+
| `prostate-seg-task` | MSD Task05 Prostate | [medicaldecathlon.com](https://medicaldecathlon.com/) | CC BY-SA 4.0 | Public | ~240 MB | Staged verified |
|
| 123 |
+
| `feta-seg-task` | FeTA | [zenodo.org/records/4541606](https://zenodo.org/records/4541606) | Research agreement | Gated | — | Externally blocked |
|
| 124 |
+
| `panther-t1-seg-task` | PANTHER | [zenodo.org/records/15192302](https://zenodo.org/records/15192302) | CC BY-NC 4.0 + access controls | Restricted | — | Externally blocked |
|
| 125 |
+
| `panther-t2-seg-task` | PANTHER | [zenodo.org/records/15192302](https://zenodo.org/records/15192302) | CC BY-NC 4.0 + access controls | Restricted | — | Externally blocked |
|
| 126 |
+
|
| 127 |
+
### Enhancement (7 tasks)
|
| 128 |
+
|
| 129 |
+
| Task ID | Upstream Dataset | Download Link | License | Access | Approx. Size | Status |
|
| 130 |
+
| --- | --- | --- | --- | --- | --- | --- |
|
| 131 |
+
| `ldct-denoising-task` | AAPM Low Dose CT Grand Challenge | [aapm.org/grandchallenge/lowdosect](https://www.aapm.org/grandchallenge/lowdosect/) | No explicit redistribution grant | Public library | ~42 MB staged | Download required |
|
| 132 |
+
| `lidc-idri-denoising-task` | LIDC-IDRI | [cancerimagingarchive.net/collection/lidc-idri](https://www.cancerimagingarchive.net/collection/lidc-idri/) | CC BY 3.0 | Public | ~136.55 GB | Acquisition ready |
|
| 133 |
+
| `deeplesion-denoising-task` | NIH DeepLesion | [nihcc.app.box.com/v/DeepLesion](https://nihcc.app.box.com/v/DeepLesion) | No explicit license | Public | Unknown | Acquisition ready |
|
| 134 |
+
| `mri-sr-task` | fastMRI | [fastmri.med.nyu.edu](https://fastmri.med.nyu.edu/) | Agreement prohibits redistribution | Application required | — | Externally blocked |
|
| 135 |
+
| `brats-t1c-sr-task` | BraTS 2023 GLI | [synapse.org/Synapse:syn51156910](https://www.synapse.org/Synapse:syn51156910/wiki/) | Controlled access | Controlled | — | Externally blocked |
|
| 136 |
+
| `ixi-t1-sr-task` | IXI T1 | [brain-development.org/ixi-dataset](https://brain-development.org/ixi-dataset/) | CC BY-SA 3.0 | Public | Not specified | Acquisition ready |
|
| 137 |
+
| `nih-cxr-sr-task` | NIH ChestXray14 | [nihcc.app.box.com/v/ChestXray-NIHCC](https://nihcc.app.box.com/v/ChestXray-NIHCC) | CC0 (NIH Kaggle) | Public | ~45.08 GB | Acquisition ready |
|
| 138 |
+
|
| 139 |
+
### VQA (9 tasks)
|
| 140 |
+
|
| 141 |
+
| Task ID | Upstream Dataset | Download Link | License | Access | Approx. Size | Status |
|
| 142 |
+
| --- | --- | --- | --- | --- | --- | --- |
|
| 143 |
+
| `pathvqa-task` | PathVQA | [huggingface.co/datasets/flaviagiammarino/path-vqa](https://huggingface.co/datasets/flaviagiammarino/path-vqa) | MIT | Public | ~785 MB | Staged verified |
|
| 144 |
+
| `vqa-rad-task` | VQA-RAD | [huggingface.co/datasets/flaviagiammarino/vqa-rad](https://huggingface.co/datasets/flaviagiammarino/vqa-rad) | CC0 1.0 | Public | ~34.5 MB | Staged verified |
|
| 145 |
+
| `medframeqa-task` | MedFrameQA | [huggingface.co/datasets/SuhaoYu1020/MedFrameQA](https://huggingface.co/datasets/SuhaoYu1020/MedFrameQA) | CC BY 4.0 | Public | ~571 MB | Staged verified |
|
| 146 |
+
| `slake-task` | SLAKE | [huggingface.co/datasets/BoKelvin/SLAKE](https://huggingface.co/datasets/BoKelvin/SLAKE) | CC BY 4.0 | Public | ~217 MB | Staged verified |
|
| 147 |
+
| `medxpertqa-mm-task` | MedXpertQA | [huggingface.co/datasets/TsinghuaC3I/MedXpertQA](https://huggingface.co/datasets/TsinghuaC3I/MedXpertQA) | MIT | Public | ~523 MB | Staged verified |
|
| 148 |
+
| `vqa-kvasir-task` | Kvasir-VQA | [huggingface.co/datasets/SimulaMet-HOST/Kvasir-VQA](https://huggingface.co/datasets/SimulaMet-HOST/Kvasir-VQA) | CC BY-NC 4.0 + benchmark permission | Permission required | ~15.18 GB | Externally blocked |
|
| 149 |
+
| `vqa-omnimedvqa-task` | OmniMedVQA | [huggingface.co/datasets/foreverbeliever/OmniMedVQA](https://huggingface.co/datasets/foreverbeliever/OmniMedVQA) | Mixed (no global license) | Mixed access | ~10.70 GB | Externally blocked |
|
| 150 |
+
| `vqa-pmc-vqa-task` | PMC-VQA | [huggingface.co/datasets/RadGenome/PMC-VQA](https://huggingface.co/datasets/RadGenome/PMC-VQA) | CC BY-SA | Public | ~21.77 GB | Staged verified |
|
| 151 |
+
| `vqa-mmmu-medical-task` | MMMU medical subsets | [huggingface.co/datasets/MMMU/MMMU](https://huggingface.co/datasets/MMMU/MMMU) | Apache-2.0 | Public | ~2.09 GB | Staged verified |
|
| 152 |
+
|
| 153 |
+
### Report Generation (5 tasks)
|
| 154 |
+
|
| 155 |
+
| Task ID | Upstream Dataset | Download Link | License | Access | Approx. Size | Status |
|
| 156 |
+
| --- | --- | --- | --- | --- | --- | --- |
|
| 157 |
+
| `mimic-cxr-report-task` | MIMIC-CXR | [physionet.org/content/mimic-cxr/2.1.0](https://physionet.org/content/mimic-cxr/2.1.0/) | DUA prohibits sharing | Credentialed DUA | 377,110 images | Externally blocked |
|
| 158 |
+
| `iu-xray-report-task` | IU Open-i | [openi.nlm.nih.gov](https://openi.nlm.nih.gov/) | No clear bulk redistribution license | Public search | Unknown | Acquisition ready |
|
| 159 |
+
| `chexpert-plus-cxr-task` | CheXpert Plus | [aimi.stanford.edu/datasets/chexpert-plus](https://aimi.stanford.edu/datasets/chexpert-plus) | No license declared by mirror | Public mirror | ~636 MB | Staged verified |
|
| 160 |
+
| `pathology-caption-100-task` | PathCap | [huggingface.co/datasets/jamessyx/PathCap](https://huggingface.co/datasets/jamessyx/PathCap) | CC BY-NC 2.0 + click-through | Auto-gated | ~13.7 GB | Staged verified |
|
| 161 |
+
| `pathology-caption-500-task` | PathCap | [huggingface.co/datasets/jamessyx/PathCap](https://huggingface.co/datasets/jamessyx/PathCap) | CC BY-NC 2.0 + click-through | Auto-gated | ~13.7 GB | Staged verified |
|
| 162 |
+
|
| 163 |
+
### Detection (4 tasks)
|
| 164 |
+
|
| 165 |
+
| Task ID | Upstream Dataset | Download Link | License | Access | Approx. Size | Status |
|
| 166 |
+
| --- | --- | --- | --- | --- | --- | --- |
|
| 167 |
+
| `vindr-cxr-det-task` | VinDr-CXR | [physionet.org/content/vindr-cxr/1.0.0](https://physionet.org/content/vindr-cxr/1.0.0/) | PhysioNet Credentialed Health Data License | Credentialed DUA | — | Externally blocked |
|
| 168 |
+
| `bccd-det-task` | BCCD | [github.com/Shenggan/BCCD_Dataset](https://github.com/Shenggan/BCCD_Dataset) | MIT | Public | ~4.95 MB | Staged verified |
|
| 169 |
+
| `dentex-det-task` | DENTEX | [huggingface.co/datasets/ibrahimhamamci/DENTEX](https://huggingface.co/datasets/ibrahimhamamci/DENTEX) | CC BY-NC-SA 4.0 | Public | ~11.84 GB | Staged verified |
|
| 170 |
+
| `grazpedwri-det-task` | GRAZPEDWRI-DX | [figshare.com/articles/dataset/GRAZPEDWRI-DX/14825193](https://figshare.com/articles/dataset/GRAZPEDWRI-DX/14825193) | CC BY 4.0 | Public | ~16.26 GB | Staged verified |
|
| 171 |
+
|
| 172 |
+
### Classification (5 tasks)
|
| 173 |
+
|
| 174 |
+
| Task ID | Upstream Dataset | Download Link | License | Access | Approx. Size | Status |
|
| 175 |
+
| --- | --- | --- | --- | --- | --- | --- |
|
| 176 |
+
| `braintumor-cls-task` | Brain Tumor MRI | [kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset](https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset) | CC BY 4.0 | Public | ~167.85 MB | Acquisition ready |
|
| 177 |
+
| `crc-histology-cls-task` | NCT-CRC-HE-100K | [zenodo.org/records/1214456](https://zenodo.org/records/1214456) | CC BY 4.0 | Public | ~11.7 GB | Acquisition ready |
|
| 178 |
+
| `patchcamelyon-cls-task` | PatchCamelyon | [github.com/basveeling/pcam](https://github.com/basveeling/pcam) | CC0 | Public | ~7.7 GB | Acquisition ready |
|
| 179 |
+
| `chest-xray-pneumonia-cls-task` | Kermany chest X-ray | [data.mendeley.com/datasets/rscbjbr9sj/2](https://data.mendeley.com/datasets/rscbjbr9sj/2) | CC BY 4.0 | Public | Not specified | Acquisition ready |
|
| 180 |
+
| `skin-lesion-cls-task` | ISIC Archive | [isic-archive.com](https://www.isic-archive.com/) | Per-image (not frozen) | Public | ~6.26 MB staged | Staged verified |
|
| 181 |
+
|
| 182 |
+
### Synthesis (4 tasks)
|
| 183 |
+
|
| 184 |
+
| Task ID | Upstream Dataset | Download Link | License | Access | Approx. Size | Status |
|
| 185 |
+
| --- | --- | --- | --- | --- | --- | --- |
|
| 186 |
+
| `synthrad2025-mrct-task` | SynthRAD2025 | [zenodo.org/records/15373853](https://zenodo.org/records/15373853) | CC BY-NC 4.0 | Public | ~14.8 GB | Acquisition ready |
|
| 187 |
+
| `ctorg-ctsr-task` | CT-ORG | [cancerimagingarchive.net/collection/ct-org](https://www.cancerimagingarchive.net/collection/ct-org/) | CC BY 3.0 | Public | Not exposed | Acquisition ready |
|
| 188 |
+
| `msd-pancreas-ctsr-task` | MSD Task07 Pancreas | [medicaldecathlon.com](https://medicaldecathlon.com/) | CC BY-SA 4.0 | Public | ~12.3 GB | Staged verified |
|
| 189 |
+
| `totalsegmentator-ctsr-task` | TotalSegmentator | [github.com/wasserth/TotalSegmentator](https://github.com/wasserth/TotalSegmentator) | CC BY 4.0 | Public | Not frozen | Acquisition ready |
|
| 190 |
+
|
| 191 |
+
## Data Acquisition Summary
|
| 192 |
+
|
| 193 |
+
| Status | Count | Description |
|
| 194 |
+
| --- | ---: | --- |
|
| 195 |
+
| Staged verified | 23 | Locally staged and layout-hashed; recipe frozen |
|
| 196 |
+
| Acquisition ready | 16 | Source and staging recipe frozen; user must download |
|
| 197 |
+
| Externally blocked | 9 | Access approval, DUA, or upstream clarification required |
|
| 198 |
+
|
| 199 |
+
## Dataset Licenses
|
| 200 |
+
|
| 201 |
+
See [docs/DATA_POLICY.md](docs/DATA_POLICY.md) for the full per-task policy
|
| 202 |
+
records. The release rule is conservative: **no dataset bytes are embedded** in
|
| 203 |
+
any task package, runtime image, or task-tier image. Every uploaded artifact is
|
| 204 |
+
code-only.
|
| 205 |
+
|
| 206 |
+
## Package Design
|
| 207 |
+
|
| 208 |
+
Each of the 48 task packages supports both `lite` and `standard` tiers; the
|
| 209 |
+
tiers share the same harness and runtime contract. The common container layer
|
| 210 |
+
remains eight shared, data-free runtime images:
|
| 211 |
+
|
| 212 |
+
- one common agent runtime used by every track; and
|
| 213 |
+
- seven track-specific evaluator runtimes, one for each track.
|
| 214 |
+
|
| 215 |
+
The execution release adds 96 thin images on top of that shared layer: one
|
| 216 |
+
immutable image for every task-tier cell. Their build IDs and API verification
|
| 217 |
+
records are frozen in `manifests/cell_images.csv` and
|
| 218 |
+
`manifests/cell_verification.csv`. The shared image inventory remains frozen in
|
| 219 |
+
`manifests/runtime_images.csv`.
|
| 220 |
+
|
| 221 |
+
Following AutoMedBench-Lite, the 96 images are exported under seven track
|
| 222 |
+
folders as `docker/<track>/automedbench-<track>-docker-image-v0.1.0.tar.gz`;
|
| 223 |
+
the local `synthetic` track uses Lite's public `synthesis` folder name. Each
|
| 224 |
+
archive is accompanied by a SHA-256 sidecar and an image inventory. Exact
|
| 225 |
+
remote sizes, hashes, and revisions are frozen in
|
| 226 |
+
`manifests/cell_archives.csv`.
|
| 227 |
+
|
| 228 |
+
## Security
|
| 229 |
+
|
| 230 |
+
No credentials, API keys, model-service tokens, personal home paths, or
|
| 231 |
+
populated runtime configuration belong in this repository or its images.
|
| 232 |
+
Source worktrees are read-only inputs; builds use fresh allow-listed staging
|
| 233 |
+
contexts made from immutable Git blobs.
|
| 234 |
+
|
| 235 |
+
## Paper
|
| 236 |
+
|
| 237 |
+
Project page: <https://automedbench.github.io/>
|
| 238 |
+
|
| 239 |
+
Paper: Junqi Liu et al., "AutoMedBench: Towards Medical AutoResearch with
|
| 240 |
+
Agentic AI Models", arXiv:2606.01961, 2026.
|
| 241 |
+
<https://arxiv.org/abs/2606.01961>
|
| 242 |
+
|
| 243 |
+
DOI: <https://doi.org/10.48550/arXiv.2606.01961>
|
| 244 |
+
|
| 245 |
+
```bibtex
|
| 246 |
+
@article{liu2026automedbench,
|
| 247 |
+
title={AutoMedBench: Towards Medical AutoResearch with Agentic AI Models},
|
| 248 |
+
author={Liu, Junqi and Song, Selena and Wang, Yuhan and Mao, Jiawei and Chen, Hardy and Huang, Xiaoke and Qi, Tianhao and Guo, Pengfei and Tang, Yucheng and He, Yufan and Zhao, Can and Myronenko, Andriy and Yang, Dong and Xu, Daguang and Zhou, Yuyin},
|
| 249 |
+
journal={arXiv preprint arXiv:2606.01961},
|
| 250 |
+
year={2026}
|
| 251 |
+
}
|
| 252 |
+
```
|
README_zh.md
ADDED
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| 1 |
+
---
|
| 2 |
+
license: other
|
| 3 |
+
tags:
|
| 4 |
+
- medical
|
| 5 |
+
- benchmark
|
| 6 |
+
- multimodal
|
| 7 |
+
- agentic
|
| 8 |
+
---
|
| 9 |
+
|
| 10 |
+
# AutoMedBench-Full-release
|
| 11 |
+
|
| 12 |
+
[](https://automedbench.github.io/) [](https://huggingface.co/spaces/MitakaKuma/AutoMedBench-Leaderboard) [](https://huggingface.co/spaces/MitakaKuma/AutoMedBench-Full-Leaderboard) [](https://arxiv.org/abs/2606.01961) [](https://github.com/AutoMedBench/AutoMedBench)
|
| 13 |
+
|
| 14 |
+
[English](README.md)
|
| 15 |
+
|
| 16 |
+
AutoMedBench 是一个面向自主医疗 AI 研究智能体的工作流感知基准。它同时评估
|
| 17 |
+
最终任务产出物和 S1-S5 研究工作流：计划、配置、验证、推理、提交。
|
| 18 |
+
|
| 19 |
+
本完整版发布包含 **7 个赛道、48 个任务**，每个任务包含 Lite 和 Standard 两个
|
| 20 |
+
层级，共 **96 个"任务 × 层级"组合**。每个组合均有预构建 Docker 镜像。数据集
|
| 21 |
+
字节**不包含在发布中** — 用户需独立准备数据并在运行时挂载。
|
| 22 |
+
|
| 23 |
+
## 如何提交
|
| 24 |
+
|
| 25 |
+
**提交邮箱：<jliu718@ucsc.edu>**
|
| 26 |
+
|
| 27 |
+
建议邮件主题：`AutoMedBench submission - <智能体/团队名称>`
|
| 28 |
+
|
| 29 |
+
| 优先级 | 操作 | 原因 |
|
| 30 |
+
| --- | --- | --- |
|
| 31 |
+
| **必须** | **在基准上至少运行 5 次重复实验。** 智能体运行可能因模型采样、工具选择、网络时序和依赖配置等因素产生变化。多次重复运行可提供比单次运行更稳定的真实性能估计。 |
|
| 32 |
+
| **必须** | **将所有输出报告和对话/转录文件打包为一个压缩文件，发送至 <jliu718@ucsc.edu>。** | 完整包让维护者可以验证最终产出物、审计工作流并检查多次运行的稳定性。 |
|
| 33 |
+
| **推荐** | **使用编码智能体来启动、监控和收集运行结果。** | 基准测试运行时间较长，可能需要查看日志、快速修复和清理对话文件。 |
|
| 34 |
+
|
| 35 |
+
## 快速开始
|
| 36 |
+
|
| 37 |
+
```bash
|
| 38 |
+
# 1. 下载赛道 Docker 镜像（以分割为例）
|
| 39 |
+
# 从本仓库下载：docker/segmentation/automedbench-segmentation-docker-image-v0.1.0.tar.gz
|
| 40 |
+
|
| 41 |
+
# 2. 加载 Docker 镜像
|
| 42 |
+
docker load -i automedbench-segmentation-docker-image-v0.1.0.tar.gz
|
| 43 |
+
|
| 44 |
+
# 3. 配置凭据
|
| 45 |
+
cp env.example .env
|
| 46 |
+
# 编辑 .env 填入你的 API 密钥
|
| 47 |
+
|
| 48 |
+
# 4. 运行任务
|
| 49 |
+
python docker/orchestrator.py \
|
| 50 |
+
--agent claude-opus-4-6 \
|
| 51 |
+
--task kidney-seg-task \
|
| 52 |
+
--tier lite \
|
| 53 |
+
--n-patients 20
|
| 54 |
+
```
|
| 55 |
+
|
| 56 |
+
Docker 镜像包含基准测试框架和评分代码。凭据仅在运行时通过 `.env` 或 shell
|
| 57 |
+
环境变量传入。数据集文件需单独挂载（参见下方[数据获取](#数据获取)）。
|
| 58 |
+
|
| 59 |
+
## Docker 镜像包
|
| 60 |
+
|
| 61 |
+
本仓库中存储了按赛道划分的预构建 Docker 镜像包：
|
| 62 |
+
|
| 63 |
+
```text
|
| 64 |
+
docker/classification/automedbench-classification-docker-image-v0.1.0.tar.gz
|
| 65 |
+
docker/detection/automedbench-detection-docker-image-v0.1.0.tar.gz
|
| 66 |
+
docker/enhancement/automedbench-enhancement-docker-image-v0.1.0.tar.gz
|
| 67 |
+
docker/report/automedbench-report-docker-image-v0.1.0.tar.gz
|
| 68 |
+
docker/segmentation/automedbench-segmentation-docker-image-v0.1.0.tar.gz
|
| 69 |
+
docker/synthesis/automedbench-synthesis-docker-image-v0.1.0.tar.gz
|
| 70 |
+
docker/vqa/automedbench-vqa-docker-image-v0.1.0.tar.gz
|
| 71 |
+
```
|
| 72 |
+
|
| 73 |
+
每个归档约 3.5 GB，包含该赛道全部 Lite + Standard 任务层级镜像。共享运行时
|
| 74 |
+
归档（`runtime/automedbench-full-runtime-0.1.0.tar.gz`，约 4 GB）提供公共
|
| 75 |
+
agent 运行时和 7 个赛道的 evaluator 镜像。
|
| 76 |
+
|
| 77 |
+
下载后加载全部镜像：
|
| 78 |
+
|
| 79 |
+
```bash
|
| 80 |
+
docker load -i runtime/automedbench-full-runtime-0.1.0.tar.gz
|
| 81 |
+
docker load -i docker/segmentation/automedbench-segmentation-docker-image-v0.1.0.tar.gz
|
| 82 |
+
# ... 按需重复其他赛道
|
| 83 |
+
```
|
| 84 |
+
|
| 85 |
+
## 发布任务（48 个任务，96 个 Lite/Standard 组合）
|
| 86 |
+
|
| 87 |
+
| 赛道 | 任务数 | 评估指标 |
|
| 88 |
+
| --- | ---: | --- |
|
| 89 |
+
| 分割 (Segmentation) | 14 | Dice（器官 + 病灶） |
|
| 90 |
+
| 图像增强 (Enhancement) | 7 | SSIM |
|
| 91 |
+
| 视觉问答 (VQA) | 9 | 答案准确率 |
|
| 92 |
+
| 报告生成 (Report) | 5 | 临床报告质量 |
|
| 93 |
+
| 检测 (Detection) | 4 | mAP@0.5 |
|
| 94 |
+
| 分类 (Classification) | 5 | 标签准确率 |
|
| 95 |
+
| 合成 (Synthesis) | 4 | SSIM |
|
| 96 |
+
|
| 97 |
+
## 数据获取
|
| 98 |
+
|
| 99 |
+
**本发布不包含数据集字节。** 每个任务引用一个上游数据集，需独立下载。下表列出
|
| 100 |
+
每个任务的数据来源、下载链接、许可和访问要求。
|
| 101 |
+
|
| 102 |
+
### 分割（14 个任务）
|
| 103 |
+
|
| 104 |
+
| 任务 ID | 上游数据集 | 下载链接 | 许可 | 访问 | 大小 | 状态 |
|
| 105 |
+
| --- | --- | --- | --- | --- | --- | --- |
|
| 106 |
+
| `kidney-seg-task` | KiTS19 | [kits19.grand-challenge.org](https://kits19.grand-challenge.org/) | CC BY-NC-SA 4.0 | 公开 | ~200 MB/例 | 可获取 |
|
| 107 |
+
| `pancreas-seg-task` | PanTS | [github.com/MrGiovanni/PanTS](https://github.com/MrGiovanni/PanTS) | CC BY-NC-ND 4.0 | 公开 | ~300–346 GB | 可获取 |
|
| 108 |
+
| `pancreas-oar-seg-task` | PanTS | [github.com/MrGiovanni/PanTS](https://github.com/MrGiovanni/PanTS) | CC BY-NC-ND 4.0 | 公开 | ~300–346 GB | 可获取 |
|
| 109 |
+
| `liver-seg-task` | MSD Task03 肝脏 | [medicaldecathlon.com](https://medicaldecathlon.com/) | 来源冲突 | 公开 | ~28.9 GB | 已验证 |
|
| 110 |
+
| `aeropath-seg-task` | AeroPath | [zenodo.org/records/10069289](https://zenodo.org/records/10069289) | CC BY 4.0 | 公开 | ~5.04 GB | 可获取 |
|
| 111 |
+
| `tsg-multiorgan-seg-task` | TotalSegmentator v2.0.1 | [zenodo.org/records/10047263](https://zenodo.org/records/10047263) | CC BY 4.0 | 公开 | ~3.24 GB | 已验证 |
|
| 112 |
+
| `colon-seg-task` | MSD Task10 结肠 | [medicaldecathlon.com](https://medicaldecathlon.com/) | CC BY-SA 4.0 | 公开 | ~6.24 GB | 已验证 |
|
| 113 |
+
| `hepaticvessel-seg-task` | MSD Task08 肝血管 | [medicaldecathlon.com](https://medicaldecathlon.com/) | CC BY-SA 4.0 | 公开 | ~9.35 GB | 已验证 |
|
| 114 |
+
| `spleen-seg-task` | MSD Task09 脾脏 | [medicaldecathlon.com](https://medicaldecathlon.com/) | CC BY-SA 4.0 | 公开 | ~1.61 GB | 已验证 |
|
| 115 |
+
| `heart-seg-task` | MSD Task02 心脏 | [medicaldecathlon.com](https://medicaldecathlon.com/) | CC BY-SA 4.0 | 公开 | ~456 MB | 已验证 |
|
| 116 |
+
| `prostate-seg-task` | MSD Task05 前列腺 | [medicaldecathlon.com](https://medicaldecathlon.com/) | CC BY-SA 4.0 | 公开 | ~240 MB | 已验证 |
|
| 117 |
+
| `feta-seg-task` | FeTA | [zenodo.org/records/4541606](https://zenodo.org/records/4541606) | 研究协议 | 需授权 | — | 外部阻塞 |
|
| 118 |
+
| `panther-t1-seg-task` | PANTHER | [zenodo.org/records/15192302](https://zenodo.org/records/15192302) | CC BY-NC 4.0 + 访问控制 | 受限 | — | 外部阻塞 |
|
| 119 |
+
| `panther-t2-seg-task` | PANTHER | [zenodo.org/records/15192302](https://zenodo.org/records/15192302) | CC BY-NC 4.0 + 访问控制 | 受限 | — | 外部阻塞 |
|
| 120 |
+
|
| 121 |
+
### 图像增强（7 个任务）
|
| 122 |
+
|
| 123 |
+
| 任务 ID | 上游数据集 | 下载链接 | 许可 | 访问 | 大小 | 状态 |
|
| 124 |
+
| --- | --- | --- | --- | --- | --- | --- |
|
| 125 |
+
| `ldct-denoising-task` | AAPM 低剂量 CT 大挑战 | [aapm.org/grandchallenge/lowdosect](https://www.aapm.org/grandchallenge/lowdosect/) | 无明确再分发许可 | 公共图书馆 | ~42 MB 暂存 | 需下载 |
|
| 126 |
+
| `lidc-idri-denoising-task` | LIDC-IDRI | [cancerimagingarchive.net/collection/lidc-idri](https://www.cancerimagingarchive.net/collection/lidc-idri/) | CC BY 3.0 | 公开 | ~136.55 GB | 可获取 |
|
| 127 |
+
| `deeplesion-denoising-task` | NIH DeepLesion | [nihcc.app.box.com/v/DeepLesion](https://nihcc.app.box.com/v/DeepLesion) | 无明确许可 | 公开 | 未知 | 可获取 |
|
| 128 |
+
| `mri-sr-task` | fastMRI | [fastmri.med.nyu.edu](https://fastmri.med.nyu.edu/) | 协议禁止再分发 | 需申请 | — | 外部阻塞 |
|
| 129 |
+
| `brats-t1c-sr-task` | BraTS 2023 GLI | [synapse.org/Synapse:syn51156910](https://www.synapse.org/Synapse:syn51156910/wiki/) | 受控访问 | 受控 | — | 外部阻塞 |
|
| 130 |
+
| `ixi-t1-sr-task` | IXI T1 | [brain-development.org/ixi-dataset](https://brain-development.org/ixi-dataset/) | CC BY-SA 3.0 | 公开 | 未明确 | 可获取 |
|
| 131 |
+
| `nih-cxr-sr-task` | NIH ChestXray14 | [nihcc.app.box.com/v/ChestXray-NIHCC](https://nihcc.app.box.com/v/ChestXray-NIHCC) | CC0 (NIH Kaggle) | 公开 | ~45.08 GB | 可获取 |
|
| 132 |
+
|
| 133 |
+
### 视觉问答（9 个任务）
|
| 134 |
+
|
| 135 |
+
| 任务 ID | 上游数据集 | 下载链接 | 许可 | 访问 | 大小 | 状态 |
|
| 136 |
+
| --- | --- | --- | --- | --- | --- | --- |
|
| 137 |
+
| `pathvqa-task` | PathVQA | [huggingface.co/datasets/flaviagiammarino/path-vqa](https://huggingface.co/datasets/flaviagiammarino/path-vqa) | MIT | 公开 | ~785 MB | 已验证 |
|
| 138 |
+
| `vqa-rad-task` | VQA-RAD | [huggingface.co/datasets/flaviagiammarino/vqa-rad](https://huggingface.co/datasets/flaviagiammarino/vqa-rad) | CC0 1.0 | 公开 | ~34.5 MB | 已验证 |
|
| 139 |
+
| `medframeqa-task` | MedFrameQA | [huggingface.co/datasets/SuhaoYu1020/MedFrameQA](https://huggingface.co/datasets/SuhaoYu1020/MedFrameQA) | CC BY 4.0 | 公开 | ~571 MB | 已验证 |
|
| 140 |
+
| `slake-task` | SLAKE | [huggingface.co/datasets/BoKelvin/SLAKE](https://huggingface.co/datasets/BoKelvin/SLAKE) | CC BY 4.0 | 公开 | ~217 MB | 已验证 |
|
| 141 |
+
| `medxpertqa-mm-task` | MedXpertQA | [huggingface.co/datasets/TsinghuaC3I/MedXpertQA](https://huggingface.co/datasets/TsinghuaC3I/MedXpertQA) | MIT | 公开 | ~523 MB | 已验证 |
|
| 142 |
+
| `vqa-kvasir-task` | Kvasir-VQA | [huggingface.co/datasets/SimulaMet-HOST/Kvasir-VQA](https://huggingface.co/datasets/SimulaMet-HOST/Kvasir-VQA) | CC BY-NC 4.0 + 基准许可 | 需许可 | ~15.18 GB | 外部阻塞 |
|
| 143 |
+
| `vqa-omnimedvqa-task` | OmniMedVQA | [huggingface.co/datasets/foreverbeliever/OmniMedVQA](https://huggingface.co/datasets/foreverbeliever/OmniMedVQA) | 混合（无统一许可） | 混合 | ~10.70 GB | 外部阻塞 |
|
| 144 |
+
| `vqa-pmc-vqa-task` | PMC-VQA | [huggingface.co/datasets/RadGenome/PMC-VQA](https://huggingface.co/datasets/RadGenome/PMC-VQA) | CC BY-SA | 公开 | ~21.77 GB | 已验证 |
|
| 145 |
+
| `vqa-mmmu-medical-task` | MMMU 医学子集 | [huggingface.co/datasets/MMMU/MMMU](https://huggingface.co/datasets/MMMU/MMMU) | Apache-2.0 | 公开 | ~2.09 GB | 已验证 |
|
| 146 |
+
|
| 147 |
+
### 报告生��（5 个任务）
|
| 148 |
+
|
| 149 |
+
| 任务 ID | 上游数据集 | 下载链接 | 许可 | 访问 | 大小 | 状态 |
|
| 150 |
+
| --- | --- | --- | --- | --- | --- | --- |
|
| 151 |
+
| `mimic-cxr-report-task` | MIMIC-CXR | [physionet.org/content/mimic-cxr/2.1.0](https://physionet.org/content/mimic-cxr/2.1.0/) | DUA 禁止共享 | 需凭据 DUA | 377,110 张图像 | 外部阻塞 |
|
| 152 |
+
| `iu-xray-report-task` | IU Open-i | [openi.nlm.nih.gov](https://openi.nlm.nih.gov/) | 无明确批量再分发许可 | 公开搜索 | 未知 | 可获取 |
|
| 153 |
+
| `chexpert-plus-cxr-task` | CheXpert Plus | [aimi.stanford.edu/datasets/chexpert-plus](https://aimi.stanford.edu/datasets/chexpert-plus) | 镜像未声明许可 | 公开镜像 | ~636 MB | 已验证 |
|
| 154 |
+
| `pathology-caption-100-task` | PathCap | [huggingface.co/datasets/jamessyx/PathCap](https://huggingface.co/datasets/jamessyx/PathCap) | CC BY-NC 2.0 + 点击同意 | 自动受限 | ~13.7 GB | 已验证 |
|
| 155 |
+
| `pathology-caption-500-task` | PathCap | [huggingface.co/datasets/jamessyx/PathCap](https://huggingface.co/datasets/jamessyx/PathCap) | CC BY-NC 2.0 + 点击同意 | 自动受限 | ~13.7 GB | 已验证 |
|
| 156 |
+
|
| 157 |
+
### 检测（4 个任务）
|
| 158 |
+
|
| 159 |
+
| 任务 ID | 上游数据集 | 下载链接 | 许可 | 访问 | 大小 | 状态 |
|
| 160 |
+
| --- | --- | --- | --- | --- | --- | --- |
|
| 161 |
+
| `vindr-cxr-det-task` | VinDr-CXR | [physionet.org/content/vindr-cxr/1.0.0](https://physionet.org/content/vindr-cxr/1.0.0/) | PhysioNet 认证健康数据许可 | 需凭据 DUA | — | 外部阻塞 |
|
| 162 |
+
| `bccd-det-task` | BCCD | [github.com/Shenggan/BCCD_Dataset](https://github.com/Shenggan/BCCD_Dataset) | MIT | 公开 | ~4.95 MB | 已验证 |
|
| 163 |
+
| `dentex-det-task` | DENTEX | [huggingface.co/datasets/ibrahimhamamci/DENTEX](https://huggingface.co/datasets/ibrahimhamamci/DENTEX) | CC BY-NC-SA 4.0 | 公开 | ~11.84 GB | 已验证 |
|
| 164 |
+
| `grazpedwri-det-task` | GRAZPEDWRI-DX | [figshare.com/articles/dataset/GRAZPEDWRI-DX/14825193](https://figshare.com/articles/dataset/GRAZPEDWRI-DX/14825193) | CC BY 4.0 | 公开 | ~16.26 GB | 已验证 |
|
| 165 |
+
|
| 166 |
+
### 分类（5 个任务）
|
| 167 |
+
|
| 168 |
+
| 任务 ID | 上游数据集 | 下载链接 | 许可 | 访问 | 大小 | 状态 |
|
| 169 |
+
| --- | --- | --- | --- | --- | --- | --- |
|
| 170 |
+
| `braintumor-cls-task` | Brain Tumor MRI | [kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset](https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset) | CC BY 4.0 | 公开 | ~167.85 MB | 可获取 |
|
| 171 |
+
| `crc-histology-cls-task` | NCT-CRC-HE-100K | [zenodo.org/records/1214456](https://zenodo.org/records/1214456) | CC BY 4.0 | 公开 | ~11.7 GB | 可获取 |
|
| 172 |
+
| `patchcamelyon-cls-task` | PatchCamelyon | [github.com/basveeling/pcam](https://github.com/basveeling/pcam) | CC0 | 公开 | ~7.7 GB | 可获取 |
|
| 173 |
+
| `chest-xray-pneumonia-cls-task` | Kermany 胸片肺炎 | [data.mendeley.com/datasets/rscbjbr9sj/2](https://data.mendeley.com/datasets/rscbjbr9sj/2) | CC BY 4.0 | 公开 | 未明确 | 可获取 |
|
| 174 |
+
| `skin-lesion-cls-task` | ISIC Archive | [isic-archive.com](https://www.isic-archive.com/) | 逐图许可（未冻结） | 公开 | ~6.26 MB 暂存 | 已验证 |
|
| 175 |
+
|
| 176 |
+
### 合成（4 个任务）
|
| 177 |
+
|
| 178 |
+
| 任务 ID | 上游数据集 | 下载链接 | 许可 | 访问 | 大小 | 状态 |
|
| 179 |
+
| --- | --- | --- | --- | --- | --- | --- |
|
| 180 |
+
| `synthrad2025-mrct-task` | SynthRAD2025 | [zenodo.org/records/15373853](https://zenodo.org/records/15373853) | CC BY-NC 4.0 | 公开 | ~14.8 GB | 可获取 |
|
| 181 |
+
| `ctorg-ctsr-task` | CT-ORG | [cancerimagingarchive.net/collection/ct-org](https://www.cancerimagingarchive.net/collection/ct-org/) | CC BY 3.0 | 公开 | 未公开 | 可获取 |
|
| 182 |
+
| `msd-pancreas-ctsr-task` | MSD Task07 胰腺 | [medicaldecathlon.com](https://medicaldecathlon.com/) | CC BY-SA 4.0 | 公开 | ~12.3 GB | 已验证 |
|
| 183 |
+
| `totalsegmentator-ctsr-task` | TotalSegmentator | [github.com/wasserth/TotalSegmentator](https://github.com/wasserth/TotalSegmentator) | CC BY 4.0 | 公开 | 未冻结 | 可获取 |
|
| 184 |
+
|
| 185 |
+
## 数据获取汇总
|
| 186 |
+
|
| 187 |
+
| 状态 | 数量 | 说明 |
|
| 188 |
+
| --- | ---: | --- |
|
| 189 |
+
| 已验证 | 23 | 本地暂存并完成布局哈希；获取流程已冻结 |
|
| 190 |
+
| 可获取 | 16 | 来源和暂存流程已冻结；用户需自行下载 |
|
| 191 |
+
| 外部阻塞 | 9 | 需审批、DUA 或上游澄清 |
|
| 192 |
+
|
| 193 |
+
## 数据集许可
|
| 194 |
+
|
| 195 |
+
完整逐任务策略记录见 [docs/DATA_POLICY.md](docs/DATA_POLICY.md)。发布规则保守：
|
| 196 |
+
**任何任务包、运行时镜像或任务层级镜像均不嵌入数据集字节。** 所有上传产物仅含代码。
|
| 197 |
+
|
| 198 |
+
## 打包设计
|
| 199 |
+
|
| 200 |
+
48 个任务包中的每一个都同时支持 `lite` 和 `standard`，两个层级共享同一任务
|
| 201 |
+
框架和运行时契约。公共容器层由 8 个共享、无数据的运行时镜像组成：
|
| 202 |
+
|
| 203 |
+
- 1 个供全部赛道共用的 agent 运行时；
|
| 204 |
+
- 7 个按赛道划分的 evaluator 运行时，每个赛道 1 个。
|
| 205 |
+
|
| 206 |
+
执行发布在该共享层之上增加 96 个轻量镜像，每个"任务 × 层级"组合对应一个不可变
|
| 207 |
+
镜像。构建 ID 与 API 验证记录冻结在 `manifests/cell_images.csv` 和
|
| 208 |
+
`manifests/cell_verification.csv`；共享镜像清单位于
|
| 209 |
+
`manifests/runtime_images.csv`。
|
| 210 |
+
|
| 211 |
+
与 AutoMedBench-Lite 一致，96 个镜像按 7 个赛道目录导出为
|
| 212 |
+
`docker/<track>/automedbench-<track>-docker-image-v0.1.0.tar.gz`；本地
|
| 213 |
+
`synthetic` 赛道在公开路径中使用 Lite 的 `synthesis` 名称。每个归档均包含
|
| 214 |
+
SHA-256 旁文件和镜像清单，远端大小、哈希与修订版本冻结在
|
| 215 |
+
`manifests/cell_archives.csv`。
|
| 216 |
+
|
| 217 |
+
## 安全
|
| 218 |
+
|
| 219 |
+
仓库及其镜像不得包含凭据、API 密钥、模型服务令牌、个人主目录路径或已填写的
|
| 220 |
+
运行时配置。源工作树仅作为只读输入；构建使用来自不可变 Git 对象、经过白名单
|
| 221 |
+
筛选的新暂存上下文。
|
| 222 |
+
|
| 223 |
+
## 论文
|
| 224 |
+
|
| 225 |
+
项目主页：<https://automedbench.github.io/>
|
| 226 |
+
|
| 227 |
+
论文：Junqi Liu et al., "AutoMedBench: Towards Medical AutoResearch with
|
| 228 |
+
Agentic AI Models", arXiv:2606.01961, 2026.
|
| 229 |
+
<https://arxiv.org/abs/2606.01961>
|
| 230 |
+
|
| 231 |
+
DOI: <https://doi.org/10.48550/arXiv.2606.01961>
|
| 232 |
+
|
| 233 |
+
```bibtex
|
| 234 |
+
@article{liu2026automedbench,
|
| 235 |
+
title={AutoMedBench: Towards Medical AutoResearch with Agentic AI Models},
|
| 236 |
+
author={Liu, Junqi and Song, Selena and Wang, Yuhan and Mao, Jiawei and Chen, Hardy and Huang, Xiaoke and Qi, Tianhao and Guo, Pengfei and Tang, Yucheng and He, Yufan and Zhao, Can and Myronenko, Andriy and Yang, Dong and Xu, Daguang and Zhou, Yuyin},
|
| 237 |
+
journal={arXiv preprint arXiv:2606.01961},
|
| 238 |
+
year={2026}
|
| 239 |
+
}
|
| 240 |
+
```
|
docker/classification/automedbench-classification-docker-image-v0.1.0.json
ADDED
|
@@ -0,0 +1,93 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"archive": "automedbench-classification-docker-image-v0.1.0.tar.gz",
|
| 3 |
+
"archive_sha256": "1f5ddef2dbec21614c48d20f0ad0c48d21b51df4f6fa9283f2da9f9e9b031ee8",
|
| 4 |
+
"archive_size": 3780481421,
|
| 5 |
+
"batch_count": 1,
|
| 6 |
+
"batch_index": 1,
|
| 7 |
+
"dataset_content_included": false,
|
| 8 |
+
"image_count": 10,
|
| 9 |
+
"images": [
|
| 10 |
+
{
|
| 11 |
+
"combination_index": 79,
|
| 12 |
+
"image_id": "sha256:4ba84490d8142ef1c086971f7d6f18a025b2185edba1aafdc00f8cd245cd83a1",
|
| 13 |
+
"package_sha256": "442bdf2304bf4fd2b138901115a480e382161714b6e201e91f2551b49115bc11",
|
| 14 |
+
"tag": "automedbench-full/cell-classification-braintumor-cls-task-lite:0.1.0",
|
| 15 |
+
"task_id": "braintumor-cls-task",
|
| 16 |
+
"tier": "lite"
|
| 17 |
+
},
|
| 18 |
+
{
|
| 19 |
+
"combination_index": 80,
|
| 20 |
+
"image_id": "sha256:5fbae86635c919e149c942637eb799544b459ab3d6273c6f3a9859fb4923987b",
|
| 21 |
+
"package_sha256": "442bdf2304bf4fd2b138901115a480e382161714b6e201e91f2551b49115bc11",
|
| 22 |
+
"tag": "automedbench-full/cell-classification-braintumor-cls-task-standard:0.1.0",
|
| 23 |
+
"task_id": "braintumor-cls-task",
|
| 24 |
+
"tier": "standard"
|
| 25 |
+
},
|
| 26 |
+
{
|
| 27 |
+
"combination_index": 81,
|
| 28 |
+
"image_id": "sha256:b1882af23d0cc56d0da84d833dcf77334b67195c4c253525d808fa698a4e7dcc",
|
| 29 |
+
"package_sha256": "46f2d3746ef95662c57d21b05baa384bf3d5906bb5430c7cc1f5684015f88aab",
|
| 30 |
+
"tag": "automedbench-full/cell-classification-crc-histology-cls-task-lite:0.1.0",
|
| 31 |
+
"task_id": "crc-histology-cls-task",
|
| 32 |
+
"tier": "lite"
|
| 33 |
+
},
|
| 34 |
+
{
|
| 35 |
+
"combination_index": 82,
|
| 36 |
+
"image_id": "sha256:18c6c76d141d37b9c8dd430e2a3cd214fc799bea2a3ab9b160533fd1c48f97f1",
|
| 37 |
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"package_sha256": "46f2d3746ef95662c57d21b05baa384bf3d5906bb5430c7cc1f5684015f88aab",
|
| 38 |
+
"tag": "automedbench-full/cell-classification-crc-histology-cls-task-standard:0.1.0",
|
| 39 |
+
"task_id": "crc-histology-cls-task",
|
| 40 |
+
"tier": "standard"
|
| 41 |
+
},
|
| 42 |
+
{
|
| 43 |
+
"combination_index": 83,
|
| 44 |
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"image_id": "sha256:1a2fcd4f5f564e251108b2053d5534af2e62900f15b9479b912666ce0961e1f1",
|
| 45 |
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"package_sha256": "59527edf718b9ae8a3026e95c2c175c5aadc377cae0da712146809804198243d",
|
| 46 |
+
"tag": "automedbench-full/cell-classification-patchcamelyon-cls-task-lite:0.1.0",
|
| 47 |
+
"task_id": "patchcamelyon-cls-task",
|
| 48 |
+
"tier": "lite"
|
| 49 |
+
},
|
| 50 |
+
{
|
| 51 |
+
"combination_index": 84,
|
| 52 |
+
"image_id": "sha256:901eba7dc7316995f66794fc1d80bb722f10ba057626ee78a0b6eae726d20c1a",
|
| 53 |
+
"package_sha256": "59527edf718b9ae8a3026e95c2c175c5aadc377cae0da712146809804198243d",
|
| 54 |
+
"tag": "automedbench-full/cell-classification-patchcamelyon-cls-task-standard:0.1.0",
|
| 55 |
+
"task_id": "patchcamelyon-cls-task",
|
| 56 |
+
"tier": "standard"
|
| 57 |
+
},
|
| 58 |
+
{
|
| 59 |
+
"combination_index": 85,
|
| 60 |
+
"image_id": "sha256:58b4d539bbecb58155bd13b1998a11a69c0eceaa861ae40545dea3c4636d1171",
|
| 61 |
+
"package_sha256": "5ffb62e3633d467057603a0aee85b8ab14d2baa2a690c8e7a5339cce2037e631",
|
| 62 |
+
"tag": "automedbench-full/cell-classification-chest-xray-pneumonia-cls-task-lite:0.1.0",
|
| 63 |
+
"task_id": "chest-xray-pneumonia-cls-task",
|
| 64 |
+
"tier": "lite"
|
| 65 |
+
},
|
| 66 |
+
{
|
| 67 |
+
"combination_index": 86,
|
| 68 |
+
"image_id": "sha256:57e1cee816cd282e496be2e0ce1ff5736d869630e5c9d045113e25d8b43893ec",
|
| 69 |
+
"package_sha256": "5ffb62e3633d467057603a0aee85b8ab14d2baa2a690c8e7a5339cce2037e631",
|
| 70 |
+
"tag": "automedbench-full/cell-classification-chest-xray-pneumonia-cls-task-standard:0.1.0",
|
| 71 |
+
"task_id": "chest-xray-pneumonia-cls-task",
|
| 72 |
+
"tier": "standard"
|
| 73 |
+
},
|
| 74 |
+
{
|
| 75 |
+
"combination_index": 87,
|
| 76 |
+
"image_id": "sha256:535cb11b26e295623ea563db77c3a8f90393f073553686d9b7110309a5c5758e",
|
| 77 |
+
"package_sha256": "2b45bf16dd206e75731ab73b60a62c0afd96d63a1ed393411684ea5300452551",
|
| 78 |
+
"tag": "automedbench-full/cell-classification-skin-lesion-cls-task-lite:0.1.0",
|
| 79 |
+
"task_id": "skin-lesion-cls-task",
|
| 80 |
+
"tier": "lite"
|
| 81 |
+
},
|
| 82 |
+
{
|
| 83 |
+
"combination_index": 88,
|
| 84 |
+
"image_id": "sha256:6eb7de95e0be85fb1c39ec742f59ea79af77bdcd9000f8fcbc262c5c2fc76240",
|
| 85 |
+
"package_sha256": "2b45bf16dd206e75731ab73b60a62c0afd96d63a1ed393411684ea5300452551",
|
| 86 |
+
"tag": "automedbench-full/cell-classification-skin-lesion-cls-task-standard:0.1.0",
|
| 87 |
+
"task_id": "skin-lesion-cls-task",
|
| 88 |
+
"tier": "standard"
|
| 89 |
+
}
|
| 90 |
+
],
|
| 91 |
+
"schema_version": 1,
|
| 92 |
+
"track": "classification"
|
| 93 |
+
}
|
docker/classification/automedbench-classification-docker-image-v0.1.0.tar.gz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1f5ddef2dbec21614c48d20f0ad0c48d21b51df4f6fa9283f2da9f9e9b031ee8
|
| 3 |
+
size 3780481421
|
docker/classification/automedbench-classification-docker-image-v0.1.0.tar.gz.sha256
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:830e7e28e99b195795db185afed0237a834ae82e490757006b4bcf490ae12990
|
| 3 |
+
size 121
|
docker/detection/automedbench-detection-docker-image-v0.1.0.json
ADDED
|
@@ -0,0 +1,77 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"archive": "automedbench-detection-docker-image-v0.1.0.tar.gz",
|
| 3 |
+
"archive_sha256": "111d60574f816079623553c8cf1fb072f91df165038552178228338abbc84d92",
|
| 4 |
+
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|
| 5 |
+
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|
| 6 |
+
"batch_index": 1,
|
| 7 |
+
"dataset_content_included": false,
|
| 8 |
+
"image_count": 8,
|
| 9 |
+
"images": [
|
| 10 |
+
{
|
| 11 |
+
"combination_index": 71,
|
| 12 |
+
"image_id": "sha256:e7b43ab642109e815526c3bf588b93d13047a1a30515a9d7933e87ebc8d168a9",
|
| 13 |
+
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|
| 14 |
+
"tag": "automedbench-full/cell-detection-vindr-cxr-det-task-lite:0.1.0",
|
| 15 |
+
"task_id": "vindr-cxr-det-task",
|
| 16 |
+
"tier": "lite"
|
| 17 |
+
},
|
| 18 |
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{
|
| 19 |
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|
| 20 |
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"image_id": "sha256:8cce5ac710ac718ef73ad91769b9afec5ce80e27ef1401b68a3149d46f9790a2",
|
| 21 |
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"package_sha256": "33a7793b21fb7dc9e0372a2930830356154c31c21c29685268ab2c0a8f1642e7",
|
| 22 |
+
"tag": "automedbench-full/cell-detection-vindr-cxr-det-task-standard:0.1.0",
|
| 23 |
+
"task_id": "vindr-cxr-det-task",
|
| 24 |
+
"tier": "standard"
|
| 25 |
+
},
|
| 26 |
+
{
|
| 27 |
+
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|
| 28 |
+
"image_id": "sha256:5df3844902712f640ee0898299e37b4c698f4a7d8ebe9bf23ed3c112fa85e950",
|
| 29 |
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"package_sha256": "1561ad83dfd9b3d0b70029b317fa38e3df50f35cd352612d5b59f68d3a29abda",
|
| 30 |
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"tag": "automedbench-full/cell-detection-bccd-det-task-lite:0.1.0",
|
| 31 |
+
"task_id": "bccd-det-task",
|
| 32 |
+
"tier": "lite"
|
| 33 |
+
},
|
| 34 |
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{
|
| 35 |
+
"combination_index": 74,
|
| 36 |
+
"image_id": "sha256:797dc663f39dc5c2b3b974ed34fdb7f6bf3a7b906dc7ec0d3d966cb4c0dfadaf",
|
| 37 |
+
"package_sha256": "1561ad83dfd9b3d0b70029b317fa38e3df50f35cd352612d5b59f68d3a29abda",
|
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|
| 75 |
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| 76 |
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|
| 77 |
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docker/synthesis/automedbench-synthesis-docker-image-v0.1.0.tar.gz
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docker/synthesis/automedbench-synthesis-docker-image-v0.1.0.tar.gz.sha256
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docker/vqa/automedbench-vqa-docker-image-v0.1.0.json
ADDED
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@@ -0,0 +1,157 @@
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{
|
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|
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{
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|
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|
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|
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|
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|
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|
| 25 |
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|
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{
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|
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|
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|
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|
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|
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"tier": "lite"
|
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|
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|
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|
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|
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"tier": "lite"
|
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"tier": "standard"
|
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|
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|
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|
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|
| 129 |
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|
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|
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|
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|
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|
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|
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|
| 157 |
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}
|
docker/vqa/automedbench-vqa-docker-image-v0.1.0.tar.gz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:17ba5d61c5466cf9036709e8f3b9cd7483fafdefc805342a1145a30053ae9fc1
|
| 3 |
+
size 3780931370
|
docker/vqa/automedbench-vqa-docker-image-v0.1.0.tar.gz.sha256
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d3ba110234a4f6c1e733fd7e8f37ceb3d7f083e75e469a33015308af24232056
|
| 3 |
+
size 110
|
docs/DATA_POLICY.md
ADDED
|
@@ -0,0 +1,44 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
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|
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|
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|
|
|
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|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Dataset release policy
|
| 2 |
+
|
| 3 |
+
AutoMedBench reports benchmark results but does not redistribute the upstream
|
| 4 |
+
dataset content referenced by the benchmark website. A private repository does
|
| 5 |
+
not override source licenses or data-use agreements.
|
| 6 |
+
|
| 7 |
+
`manifests/data_policy.csv` freezes one policy record for each of the 48 tasks:
|
| 8 |
+
|
| 9 |
+
- `redistributable`: a source appears to grant redistribution under the listed
|
| 10 |
+
license; attribution and all license conditions still apply;
|
| 11 |
+
- `download_required`: users must obtain the data from the upstream source;
|
| 12 |
+
- `restricted`: access is gated or credentialed or redistribution is
|
| 13 |
+
prohibited;
|
| 14 |
+
- `unknown`: no sufficient redistribution grant has been verified.
|
| 15 |
+
|
| 16 |
+
The release rule is conservative: no dataset bytes are embedded in any of the
|
| 17 |
+
48 task packages, the eight shared runtime images, or the 96 thin task-tier
|
| 18 |
+
images. Every uploaded artifact is code-only. Runtime data is mounted from a
|
| 19 |
+
local directory prepared independently by the authorized user. The shared
|
| 20 |
+
runtime inventory is frozen in `manifests/runtime_images.csv`; task-tier image
|
| 21 |
+
and archive identities are frozen in `manifests/cell_images.csv` and
|
| 22 |
+
`manifests/cell_archives.csv`.
|
| 23 |
+
|
| 24 |
+
`manifests/dataset_resolution.csv` resolves every task to one auditable state:
|
| 25 |
+
23 task rows are locally staged and layout-hashed, 16 are acquisition-ready
|
| 26 |
+
from a frozen source/recipe, and nine are externally blocked by an approval,
|
| 27 |
+
DUA, or mixed-source permission requirement. These local readiness records do
|
| 28 |
+
not grant redistribution rights and no staged dataset directory is uploaded.
|
| 29 |
+
|
| 30 |
+
Before any task can be called release-ready:
|
| 31 |
+
|
| 32 |
+
1. the upstream source and immutable revision must be frozen;
|
| 33 |
+
2. its license or access agreement must be retained with the release audit;
|
| 34 |
+
3. selected case IDs and deterministic staging checksums must be recorded;
|
| 35 |
+
4. restricted users must acquire the data independently;
|
| 36 |
+
5. the staged layout must pass the exact-secret and personal-path scan.
|
| 37 |
+
|
| 38 |
+
Known immediate gates include the declared LiTS versus pinned MSD liver
|
| 39 |
+
provenance distinction; FeTA, PANTHER, fastMRI, BraTS, Kvasir-VQA,
|
| 40 |
+
OmniMedVQA, MIMIC-CXR, and VinDr-CXR access restrictions; and unclear
|
| 41 |
+
CheXpert Plus and ISIC subset licenses. PathCap is staged for authorized local
|
| 42 |
+
use with distinct 100/500 ID lists but remains prohibited from redistribution.
|
| 43 |
+
The 15 website tasks absent from locked source branches now have explicitly
|
| 44 |
+
identified `release_owned_v1` harnesses rather than being reported as missing.
|
docs/EXECUTION_PLAN.md
ADDED
|
@@ -0,0 +1,88 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Full-release 96-cell execution plan
|
| 2 |
+
|
| 3 |
+
## Objective
|
| 4 |
+
|
| 5 |
+
Publish and verify one Docker image for every frozen task-tier cell in
|
| 6 |
+
`manifests/task_matrix.csv`: 48 tasks times `lite` and `standard`, for 96
|
| 7 |
+
images total.
|
| 8 |
+
|
| 9 |
+
The Lite release is the packaging reference: downloadable Docker archives are
|
| 10 |
+
grouped by track. The Full release preserves its stricter isolation and data
|
| 11 |
+
policy: task images contain code, prompts, contracts, and provenance only.
|
| 12 |
+
Dataset bytes are mounted at runtime and are never embedded in an uploaded
|
| 13 |
+
image.
|
| 14 |
+
|
| 15 |
+
## Artifact layout
|
| 16 |
+
|
| 17 |
+
- Build one immutable task image per matrix row, tagged under the
|
| 18 |
+
`automedbench-full/` namespace and locked to one task and one tier.
|
| 19 |
+
- Retain the common agent runtime and seven track evaluator runtimes.
|
| 20 |
+
- Group exports into the same seven per-track paths and archive names used by
|
| 21 |
+
AutoMedBench-Lite. Each archive contains all task-tier images for its track;
|
| 22 |
+
the largest contains 28 images. The already-published runtime archive
|
| 23 |
+
supplies the shared agent and seven evaluator images.
|
| 24 |
+
- Process upload archives serially. Keep each local archive until the private
|
| 25 |
+
Hugging Face remote reports the same size and SHA-256, then remove only that
|
| 26 |
+
verified archive and its uniquely namespaced task tags.
|
| 27 |
+
- Never run a global Docker prune or remove unrelated images, containers,
|
| 28 |
+
volumes, or caches.
|
| 29 |
+
|
| 30 |
+
## Dataset resolution
|
| 31 |
+
|
| 32 |
+
For every task, record one of these outcomes with source revision, license,
|
| 33 |
+
selected IDs, layout checksum, and evidence:
|
| 34 |
+
|
| 35 |
+
1. `staged_verified`: authorized source data were deterministically staged and
|
| 36 |
+
scanned.
|
| 37 |
+
2. `acquisition_ready`: the source and staging recipe are frozen, but an
|
| 38 |
+
authorized user must supply gated data.
|
| 39 |
+
3. `externally_blocked`: access approval, a DUA, or upstream clarification is
|
| 40 |
+
required and cannot be substituted by a private upload.
|
| 41 |
+
|
| 42 |
+
Restricted or unclear-license data may be used locally only when access is
|
| 43 |
+
already authorized. They must not be uploaded. Synthetic inputs may verify a
|
| 44 |
+
container contract, but never change a task's dataset readiness status.
|
| 45 |
+
|
| 46 |
+
## Verification gates
|
| 47 |
+
|
| 48 |
+
Each of the 96 cells must pass:
|
| 49 |
+
|
| 50 |
+
1. task schema, internal checksums, path safety, and credential scan;
|
| 51 |
+
2. Docker build with a digest-pinned base and immutable task/tier labels;
|
| 52 |
+
3. non-root container self-test and task/tier identity check;
|
| 53 |
+
4. prompt and output-contract rendering against a staged or synthetic public
|
| 54 |
+
item;
|
| 55 |
+
5. a bounded ChatGPT API workflow smoke run covering S1 and S2 only;
|
| 56 |
+
6. termination before S3 validation starts;
|
| 57 |
+
7. exported-archive OCI graph, layer digest, tag inventory, and secret scan;
|
| 58 |
+
8. private remote size and SHA-256 equality after upload.
|
| 59 |
+
|
| 60 |
+
S1-S2 smoke results are launch/readiness evidence only. They are not benchmark
|
| 61 |
+
scores and must not be presented as task completion.
|
| 62 |
+
|
| 63 |
+
## Execution order
|
| 64 |
+
|
| 65 |
+
1. Audit local/remote access, disk, Docker, GPU visibility, and credentials
|
| 66 |
+
without printing sensitive values.
|
| 67 |
+
2. Resolve public datasets first; freeze acquisition recipes for gated tasks;
|
| 68 |
+
update readiness records from evidence.
|
| 69 |
+
3. Implement and test the task-image builder, S1-S2 verification mode, archive
|
| 70 |
+
exporter, and remote verifier.
|
| 71 |
+
4. Build and verify all 96 images.
|
| 72 |
+
5. Run S1-S2 smoke verification in bounded batches, stopping before S3.
|
| 73 |
+
6. Export and upload one track at a time, verifying the remote before cleanup.
|
| 74 |
+
7. Audit the final 96-image inventory and update release documentation.
|
| 75 |
+
|
| 76 |
+
## Known environmental constraints at plan freeze
|
| 77 |
+
|
| 78 |
+
- LLM verification uses the configured remote ChatGPT-compatible API only;
|
| 79 |
+
host GPUs are intentionally not used.
|
| 80 |
+
- Docker is available through passwordless `sudo`; the user is not in the
|
| 81 |
+
`docker` group.
|
| 82 |
+
- The Docker daemon does not currently have NVIDIA Container Toolkit support.
|
| 83 |
+
This is not a release blocker because the requested S1-S2 verification is
|
| 84 |
+
CPU-safe and uses the remote API; verification launches omit `--gpus`.
|
| 85 |
+
- The configured ChatGPT-compatible endpoint and private Hugging Face token
|
| 86 |
+
both authenticate successfully.
|
| 87 |
+
- Gated/DUA datasets remain external dependencies even when the build and
|
| 88 |
+
upload pipeline is otherwise complete.
|
docs/RELEASE_STATUS.md
ADDED
|
@@ -0,0 +1,141 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Full-release status
|
| 2 |
+
|
| 3 |
+
The release target is frozen to the task selector published by the
|
| 4 |
+
AutoMedBench website at commit
|
| 5 |
+
`1e6471746c94adfd53f552a7bc0b81386f5a5f78`:
|
| 6 |
+
|
| 7 |
+
- 48 unique tasks across seven tracks;
|
| 8 |
+
- exactly two included tiers, `lite` and `standard`;
|
| 9 |
+
- 96 task-tier combinations;
|
| 10 |
+
- the segmentation-only `pro` UI option is excluded because its 14 result
|
| 11 |
+
arrays are empty and the website disables it.
|
| 12 |
+
|
| 13 |
+
The exact ordered rows are in `manifests/task_matrix.csv`. Run
|
| 14 |
+
`python scripts/verify_matrix.py` to verify the counts and invariants.
|
| 15 |
+
|
| 16 |
+
## Source readiness
|
| 17 |
+
|
| 18 |
+
The locked source branch tips contain canonical task configuration directories
|
| 19 |
+
for 33 of the 48 published tasks. Fifteen website tasks are not present in
|
| 20 |
+
those refs:
|
| 21 |
+
|
| 22 |
+
- enhancement: 5;
|
| 23 |
+
- VQA: 4;
|
| 24 |
+
- report generation: 3;
|
| 25 |
+
- classification: 3.
|
| 26 |
+
|
| 27 |
+
The missing harnesses are:
|
| 28 |
+
|
| 29 |
+
- enhancement: `lidc-idri-denoising-task`,
|
| 30 |
+
`deeplesion-denoising-task`, `brats-t1c-sr-task`, `ixi-t1-sr-task`, and
|
| 31 |
+
`nih-cxr-sr-task`;
|
| 32 |
+
- VQA: `vqa-kvasir-task`, `vqa-omnimedvqa-task`, `vqa-pmc-vqa-task`, and
|
| 33 |
+
`vqa-mmmu-medical-task`;
|
| 34 |
+
- report generation: `iu-xray-report-task`,
|
| 35 |
+
`pathology-caption-100-task`, and `pathology-caption-500-task`;
|
| 36 |
+
- classification: `crc-histology-cls-task`,
|
| 37 |
+
`patchcamelyon-cls-task`, and `chest-xray-pneumonia-cls-task`.
|
| 38 |
+
|
| 39 |
+
An exhaustive search covered all local refs, 131 reachable commits, 6,729 Git
|
| 40 |
+
objects, path history, blob content, and unreachable objects. It found no
|
| 41 |
+
recoverable complete harness for these tasks. Historical results preserve the
|
| 42 |
+
three classification IDs, and an older report commit contains only incomplete
|
| 43 |
+
PathCap staging code; neither is a runnable task definition.
|
| 44 |
+
|
| 45 |
+
The release now supplies those 15 definitions as `release_owned_v1`
|
| 46 |
+
reconstructions, not as purported canonical source. They are tied to website
|
| 47 |
+
commit `1e6471746c94adfd53f552a7bc0b81386f5a5f78`, recorded one-for-one in
|
| 48 |
+
`manifests/release_owned_tasks.csv`, and keep their unresolved data splits,
|
| 49 |
+
permissions, baselines, and metric assets explicit. The frozen matrix therefore
|
| 50 |
+
contains 33 `committed` tasks and 15 `release_owned` tasks, with both Lite and
|
| 51 |
+
Standard rows for all 48.
|
| 52 |
+
|
| 53 |
+
Every task now has a concrete record in
|
| 54 |
+
`manifests/dataset_resolution.csv`: 23 task rows are `staged_verified`, 16 are
|
| 55 |
+
`acquisition_ready`, and nine are `externally_blocked`. The staged rows occupy
|
| 56 |
+
22 unique local dataset directories because the PathCap 100/500 tasks share a
|
| 57 |
+
pinned 500-case source with distinct ID lists. Local staging contains 28,916
|
| 58 |
+
files and about 10.09 GB of logical data. It includes pinned MSD, VQA,
|
| 59 |
+
detection, MMMU, PMC-VQA, and authorized PathCap additions beyond the original
|
| 60 |
+
seven Lite snapshots.
|
| 61 |
+
|
| 62 |
+
Staged trees pass regular-file, symlink, sensitive-filename, path, selection,
|
| 63 |
+
and layout-hash checks. Restricted bytes remain local and Git-ignored. The
|
| 64 |
+
matrix no longer contains `not_found`; acquisition-ready and externally
|
| 65 |
+
blocked states remain visible rather than being replaced with synthetic data.
|
| 66 |
+
|
| 67 |
+
All 48 task definitions build reproducibly into 48 data-free task archives
|
| 68 |
+
(1,451,034 bytes total). Each archive contains both Lite and Standard
|
| 69 |
+
scaffolding, an internal member checksum manifest, and no dataset directory. A
|
| 70 |
+
second clean build produced byte-identical archives and catalog. All 1,568
|
| 71 |
+
archive members pass exact-secret, token-pattern, host-path, path-safety, and
|
| 72 |
+
internal-checksum verification. A separate runtime gate renders every package
|
| 73 |
+
in both tiers and exactly matches all 96 matrix cells. The package manifest
|
| 74 |
+
records zero missing definitions; readiness gates remain visible in the
|
| 75 |
+
release-owned task configs.
|
| 76 |
+
|
| 77 |
+
## Runtime and task-tier image architecture
|
| 78 |
+
|
| 79 |
+
The release has exactly eight logical shared runtime images, frozen in
|
| 80 |
+
`manifests/runtime_images.csv`:
|
| 81 |
+
|
| 82 |
+
- one common agent runtime covering all 48 tasks and both tiers;
|
| 83 |
+
- seven track-specific evaluator runtimes covering 14, 7, 9, 5, 4, 5, and 4
|
| 84 |
+
tasks respectively.
|
| 85 |
+
|
| 86 |
+
The requested execution layer adds 96 thin task-tier images, one per frozen
|
| 87 |
+
matrix row. The builder disables non-deterministic provenance attestations and
|
| 88 |
+
normalizes context timestamps; two clean builds produce the same 96 image IDs.
|
| 89 |
+
Every image passes a non-root self-test. A final CPU-only remote-API smoke run
|
| 90 |
+
covers S1 and S2 for all 96 IDs, records `stopped_before_stage=s3`, and never
|
| 91 |
+
requests a host GPU. Build and verification identities are frozen in
|
| 92 |
+
`manifests/cell_images.csv` and `manifests/cell_verification.csv`.
|
| 93 |
+
|
| 94 |
+
All eight are data-free, built, self-tested, privately uploaded, and recorded
|
| 95 |
+
as `uploaded_verified`. The combined
|
| 96 |
+
4,297,282,868-byte archive has SHA-256
|
| 97 |
+
`b9b7bea8e0e3cb0a03673f00d5b98ba6dfcc3c8329f37f26cf440cec980d38e8`.
|
| 98 |
+
The archive audit covered 44 unique layers, 143,878 layer members, 88,216
|
| 99 |
+
regular files, and 13,749,492,925 bytes without an exact match to any of the
|
| 100 |
+
four locally loaded sensitive values. The eight shared images remain the
|
| 101 |
+
common base beneath the 96 small task-tier layers rather than being copied as
|
| 102 |
+
separate full runtimes.
|
| 103 |
+
|
| 104 |
+
The private Hugging Face repository reports the same LFS size and SHA-256 at
|
| 105 |
+
revision `cbeb96a85325da6dbe039a5a0cf6053293aa7ba6`. Authenticated metadata
|
| 106 |
+
confirms `private=true`, and an anonymous API request remains denied. All 48
|
| 107 |
+
task archives were likewise verified after five commits of
|
| 108 |
+
`10 + 10 + 10 + 10 + 8` files.
|
| 109 |
+
|
| 110 |
+
The seven task-tier archives contain all 96 image tags and total
|
| 111 |
+
26,464,155,973 bytes. Each remote LFS object matches the size and SHA-256 in
|
| 112 |
+
`manifests/cell_archives.csv`; the independent post-publication audit passed at
|
| 113 |
+
cell-artifact revision `e23ec6423db3833b0725ba021f222e8277d19a03` with the
|
| 114 |
+
repository still private and anonymous access denied.
|
| 115 |
+
|
| 116 |
+
Only after those checks, the exact local runtime archive and sidecar plus the
|
| 117 |
+
eight `automedbench-full/*:0.1.0` image tags were removed. No shared or global
|
| 118 |
+
Docker prune was run. The local task packages are retained because their total
|
| 119 |
+
compressed size is only 1,451,034 bytes and they support repeatable audits.
|
| 120 |
+
|
| 121 |
+
The shared archive passed tag inventory, OCI graph, blob digest, diff-ID, path,
|
| 122 |
+
historical-layer, and exact-secret checks. Its two upstream bases are
|
| 123 |
+
digest-pinned and their nine ordered diff IDs are locked; heuristic token/path
|
| 124 |
+
checks apply to every release-owned layer. The same fail-closed checks apply
|
| 125 |
+
to every task-tier track archive. Definition coverage is complete,
|
| 126 |
+
but task readiness is separate: reconstructed tasks remain blocked where their
|
| 127 |
+
manifests record unresolved data or metric assets, and every runnable task
|
| 128 |
+
receives independently acquired data through a runtime mount rather than
|
| 129 |
+
through an image layer.
|
| 130 |
+
|
| 131 |
+
## Packaging rule
|
| 132 |
+
|
| 133 |
+
Task-tier exports align with AutoMedBench-Lite: seven per-track paths named
|
| 134 |
+
`docker/<track>/automedbench-<track>-docker-image-v0.1.0.tar.gz`, with
|
| 135 |
+
`synthesis` used for the local `synthetic` track. The archives contain
|
| 136 |
+
`28 + 14 + 18 + 10 + 8 + 10 + 8 = 96` image tags across segmentation,
|
| 137 |
+
enhancement, VQA, report, detection, classification, and synthesis. Each is
|
| 138 |
+
retained locally until the private remote reports the same size and LFS
|
| 139 |
+
SHA-256; only then are that track's archive, sidecar, and uniquely namespaced
|
| 140 |
+
tags removed. Shared Docker state is never globally pruned. Exact remote
|
| 141 |
+
identities are recorded in `manifests/cell_archives.csv`.
|
manifests/cell_archives.csv
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
track,batch_index,batch_count,image_count,archive,archive_size,archive_sha256,remote_path,remote_revision,status
|
| 2 |
+
classification,1,1,10,automedbench-classification-docker-image-v0.1.0.tar.gz,3780481421,1f5ddef2dbec21614c48d20f0ad0c48d21b51df4f6fa9283f2da9f9e9b031ee8,docker/classification/automedbench-classification-docker-image-v0.1.0.tar.gz,280c7eaefafe364cdf4761e3b029dfa5e4982178,uploaded_verified
|
| 3 |
+
detection,1,1,8,automedbench-detection-docker-image-v0.1.0.tar.gz,3780464459,111d60574f816079623553c8cf1fb072f91df165038552178228338abbc84d92,docker/detection/automedbench-detection-docker-image-v0.1.0.tar.gz,f87325dc19743e16011797168467f3bbc5b72c04,uploaded_verified
|
| 4 |
+
enhancement,1,1,14,automedbench-enhancement-docker-image-v0.1.0.tar.gz,3780506991,7369a1c4876c6a20dbce508e936e36a07b6ee37ae23b5c055d6347e651fbe1fb,docker/enhancement/automedbench-enhancement-docker-image-v0.1.0.tar.gz,e7f6c40b075918b990162f72fddcf104bdfde4e1,uploaded_verified
|
| 5 |
+
report,1,1,10,automedbench-report-docker-image-v0.1.0.tar.gz,3780467236,e6e03d783313725c5d85870cbbda63f9868237bb24c1e64ebceffe4cd9d31671,docker/report/automedbench-report-docker-image-v0.1.0.tar.gz,517b6ed838aafe274647fbafdfb79032abfdada3,uploaded_verified
|
| 6 |
+
segmentation,1,1,28,automedbench-segmentation-docker-image-v0.1.0.tar.gz,3780868882,c814596c646784c9588541f81cc950fc5ad6c67430a219759a3af514a93b3447,docker/segmentation/automedbench-segmentation-docker-image-v0.1.0.tar.gz,76466712e87e61057bad8e71935b9082623f7d13,uploaded_verified
|
| 7 |
+
synthesis,1,1,8,automedbench-synthesis-docker-image-v0.1.0.tar.gz,3780435614,f1474a759eba362c05d9c77b4da8c253061d002c980d0e3f70d939d076a5123b,docker/synthesis/automedbench-synthesis-docker-image-v0.1.0.tar.gz,e23ec6423db3833b0725ba021f222e8277d19a03,uploaded_verified
|
| 8 |
+
vqa,1,1,18,automedbench-vqa-docker-image-v0.1.0.tar.gz,3780931370,17ba5d61c5466cf9036709e8f3b9cd7483fafdefc805342a1145a30053ae9fc1,docker/vqa/automedbench-vqa-docker-image-v0.1.0.tar.gz,ec1b8912eff6c3aa62fc9233c3daff786e76cd12,uploaded_verified
|
manifests/cell_images.csv
ADDED
|
@@ -0,0 +1,97 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
combination_index,track,website_task_id,evaluator_task_id,tier,image_tag,image_id,package_sha256,dataset_content_included,status
|
| 2 |
+
1,segmentation,kidney,kidney-seg-task,lite,automedbench-full/cell-segmentation-kidney-seg-task-lite:0.1.0,sha256:05b252d47d86eaa9c642c7e1a1c1cec68f525a2d071591e4fd1b799fcc471b57,c176cc4aa9072bd8748fb341f44faae84fafac6d7bbadc6578bda24aff446013,false,built_verified
|
| 3 |
+
2,segmentation,kidney,kidney-seg-task,standard,automedbench-full/cell-segmentation-kidney-seg-task-standard:0.1.0,sha256:7bfa4547d98be063664566efed35f4e15860e15327f7ec0413be93f9164862ce,c176cc4aa9072bd8748fb341f44faae84fafac6d7bbadc6578bda24aff446013,false,built_verified
|
| 4 |
+
3,segmentation,pancreas,pancreas-seg-task,lite,automedbench-full/cell-segmentation-pancreas-seg-task-lite:0.1.0,sha256:c75551ef11fd0b066f123b766f817942ee9b288f1e5ea00120bae03449de641e,deaae28d23b5d07d40b2b402709b4661665f93e16904d555f5e1f2b67347dbf4,false,built_verified
|
| 5 |
+
4,segmentation,pancreas,pancreas-seg-task,standard,automedbench-full/cell-segmentation-pancreas-seg-task-standard:0.1.0,sha256:fd68f369f52d995fb3e70ddfe7e2490a5580c8d43d3199103ae5aee9aa193060,deaae28d23b5d07d40b2b402709b4661665f93e16904d555f5e1f2b67347dbf4,false,built_verified
|
| 6 |
+
5,segmentation,pancreas_oar,pancreas-oar-seg-task,lite,automedbench-full/cell-segmentation-pancreas-oar-seg-task-lite:0.1.0,sha256:46a8d1fc6a54e6d3de21780ce887882cf6b07059ab05a3e3c1c19d2ce848443c,5b5d91b220c752970e3c9a5ac3cadf28a9e98e6cf9d35d8c472eec201db50beb,false,built_verified
|
| 7 |
+
6,segmentation,pancreas_oar,pancreas-oar-seg-task,standard,automedbench-full/cell-segmentation-pancreas-oar-seg-task-standard:0.1.0,sha256:f46e4826740c097ef59952b5af1702ad9ec36dcd1f8def5ae52d65df9133fe01,5b5d91b220c752970e3c9a5ac3cadf28a9e98e6cf9d35d8c472eec201db50beb,false,built_verified
|
| 8 |
+
7,segmentation,liver,liver-seg-task,lite,automedbench-full/cell-segmentation-liver-seg-task-lite:0.1.0,sha256:731dce1cf740a32692514015277d26441d1aadfde3ec9c686c663c1cabac4dfd,58abecb198c534e3148e245b757e9d205922e012ea69422cf219d66558f1868e,false,built_verified
|
| 9 |
+
8,segmentation,liver,liver-seg-task,standard,automedbench-full/cell-segmentation-liver-seg-task-standard:0.1.0,sha256:72738ef1f06d6d86b4cdbe1968625c996495c3c3685972bb96d5fbca8d7553b2,58abecb198c534e3148e245b757e9d205922e012ea69422cf219d66558f1868e,false,built_verified
|
| 10 |
+
9,segmentation,aeropath,aeropath-seg-task,lite,automedbench-full/cell-segmentation-aeropath-seg-task-lite:0.1.0,sha256:8078390a79d79bcd396a2bda9bf166413e016865de5cc3df52db96b8bf792b68,69974567a0f09a9910ceab4100756f1b5d541528172f4e9bdcc8d90c096dbe72,false,built_verified
|
| 11 |
+
10,segmentation,aeropath,aeropath-seg-task,standard,automedbench-full/cell-segmentation-aeropath-seg-task-standard:0.1.0,sha256:6000e7218365b3b999701ba09659b18ea714336b8891039f240b55e8d35db45f,69974567a0f09a9910ceab4100756f1b5d541528172f4e9bdcc8d90c096dbe72,false,built_verified
|
| 12 |
+
11,segmentation,totalsegmentator,tsg-multiorgan-seg-task,lite,automedbench-full/cell-segmentation-tsg-multiorgan-seg-task-lite:0.1.0,sha256:4f13044db234c89ff1d4fbb19d22cd7b634564d4dbef8a1a808a92b308368a38,8822bbbe796c6fa098d8fab10094317dc622250388060ebfdf24a16aad6d6cee,false,built_verified
|
| 13 |
+
12,segmentation,totalsegmentator,tsg-multiorgan-seg-task,standard,automedbench-full/cell-segmentation-tsg-multiorgan-seg-task-standard:0.1.0,sha256:d61987eb48bb9d2e25b6cb00e1c04baf4d70d7b4bbcf4eba5e0f612777f89d7a,8822bbbe796c6fa098d8fab10094317dc622250388060ebfdf24a16aad6d6cee,false,built_verified
|
| 14 |
+
13,segmentation,colon,colon-seg-task,lite,automedbench-full/cell-segmentation-colon-seg-task-lite:0.1.0,sha256:9885556f522740f931875118cd4b1fddb937878b28743cc94bfa96ac71b9c8ea,858c85303b5f67a0d38b9e84ffe44511917af6551e47584bd0624a3bf232c181,false,built_verified
|
| 15 |
+
14,segmentation,colon,colon-seg-task,standard,automedbench-full/cell-segmentation-colon-seg-task-standard:0.1.0,sha256:6afb0f86b785398e841101f17f47072f3e559d19311e10435c4f50a38184e715,858c85303b5f67a0d38b9e84ffe44511917af6551e47584bd0624a3bf232c181,false,built_verified
|
| 16 |
+
15,segmentation,hepaticvessel,hepaticvessel-seg-task,lite,automedbench-full/cell-segmentation-hepaticvessel-seg-task-lite:0.1.0,sha256:87b25d99018fe78db4a75a2288d972acc2a3f793d5b44a7ffee2d52b002a7a89,1000c87bce0cbf549c94af1408a96295741284d67a5a0e105707ff23870156d4,false,built_verified
|
| 17 |
+
16,segmentation,hepaticvessel,hepaticvessel-seg-task,standard,automedbench-full/cell-segmentation-hepaticvessel-seg-task-standard:0.1.0,sha256:ccb0b7cbf8ee6d7e218a72a91bf0113d63d47e75933886052403151410134eb6,1000c87bce0cbf549c94af1408a96295741284d67a5a0e105707ff23870156d4,false,built_verified
|
| 18 |
+
17,segmentation,spleen,spleen-seg-task,lite,automedbench-full/cell-segmentation-spleen-seg-task-lite:0.1.0,sha256:fbfacf3fe93a820387eddb87b2e6b3372f10e224152860aabdbb11e455da1fae,7a75ce7a9f5275f64243a416d13435087edc7eb610c60a23eb03bac08fafcb00,false,built_verified
|
| 19 |
+
18,segmentation,spleen,spleen-seg-task,standard,automedbench-full/cell-segmentation-spleen-seg-task-standard:0.1.0,sha256:e97ffaa77982fd29fc153420315d8b5f72ba8827fc3f97276893dbb1a01d2d36,7a75ce7a9f5275f64243a416d13435087edc7eb610c60a23eb03bac08fafcb00,false,built_verified
|
| 20 |
+
19,segmentation,feta,feta-seg-task,lite,automedbench-full/cell-segmentation-feta-seg-task-lite:0.1.0,sha256:98919b3742f67f4db001e4b50676d53d8cb00a8c5a727e9e6e3c86888a57e94a,03af6ffeada7293fd3090712bd5b4d4746227383d2ca3fa48554a32d3c1905e2,false,built_verified
|
| 21 |
+
20,segmentation,feta,feta-seg-task,standard,automedbench-full/cell-segmentation-feta-seg-task-standard:0.1.0,sha256:0a5f84432d67fdd86119eb82224d095f1ea13d8a159a50cb67e63554f4c11ce9,03af6ffeada7293fd3090712bd5b4d4746227383d2ca3fa48554a32d3c1905e2,false,built_verified
|
| 22 |
+
21,segmentation,panther_t1,panther-t1-seg-task,lite,automedbench-full/cell-segmentation-panther-t1-seg-task-lite:0.1.0,sha256:3f15e665d4cfde2e12a5849395871355929e47a8282c79c62015db7121fe4542,eb1a80bd3deb5a9772ff79cecf3674fd752752a33b8fd87d0d5b17d9c44f9ace,false,built_verified
|
| 23 |
+
22,segmentation,panther_t1,panther-t1-seg-task,standard,automedbench-full/cell-segmentation-panther-t1-seg-task-standard:0.1.0,sha256:b7dbc603eb157b7eca789eb3e0e86041caabb62efd65590a6844fedf2472304d,eb1a80bd3deb5a9772ff79cecf3674fd752752a33b8fd87d0d5b17d9c44f9ace,false,built_verified
|
| 24 |
+
23,segmentation,panther_t2,panther-t2-seg-task,lite,automedbench-full/cell-segmentation-panther-t2-seg-task-lite:0.1.0,sha256:4be0ffe4a878c0d2e12fa64cc47e64d9cedef0fed94b70688565ed09cec5c10c,9a7b4a23865e45d794d803b93320408b19f9c6099a7c106f39bba6122b57b5b6,false,built_verified
|
| 25 |
+
24,segmentation,panther_t2,panther-t2-seg-task,standard,automedbench-full/cell-segmentation-panther-t2-seg-task-standard:0.1.0,sha256:a9d2c9f0aa61f4030ab831f65b34e100f130ee8271a5c5845face4a54b3f9951,9a7b4a23865e45d794d803b93320408b19f9c6099a7c106f39bba6122b57b5b6,false,built_verified
|
| 26 |
+
25,segmentation,heart,heart-seg-task,lite,automedbench-full/cell-segmentation-heart-seg-task-lite:0.1.0,sha256:91ed22656a681d03b21f86ce1d355f221298affca41fe295f3201b0ea36203ad,0bc35998ad400b0f20f8f79a6d5f5febabaa03be0580264353f8df8584624ba9,false,built_verified
|
| 27 |
+
26,segmentation,heart,heart-seg-task,standard,automedbench-full/cell-segmentation-heart-seg-task-standard:0.1.0,sha256:766a0948bf8289813df8f03b7f74fe951c653b29ef5efe722355ab4a8940ebba,0bc35998ad400b0f20f8f79a6d5f5febabaa03be0580264353f8df8584624ba9,false,built_verified
|
| 28 |
+
27,segmentation,prostate,prostate-seg-task,lite,automedbench-full/cell-segmentation-prostate-seg-task-lite:0.1.0,sha256:b708e6d89ab494a06a9c248d048b654479b8430e73af0daa1621b36990bd9f16,5783900cff8611f47dd5e2ca7fdc0a30e0e2f0446d914f57b80cf54551ef4fde,false,built_verified
|
| 29 |
+
28,segmentation,prostate,prostate-seg-task,standard,automedbench-full/cell-segmentation-prostate-seg-task-standard:0.1.0,sha256:286a7ee554961cfd408894a6fe3b3d22873deb756e461bd3359c44b6b54719bc,5783900cff8611f47dd5e2ca7fdc0a30e0e2f0446d914f57b80cf54551ef4fde,false,built_verified
|
| 30 |
+
29,enhancement,ldct-denoising-task,ldct-denoising-task,lite,automedbench-full/cell-enhancement-ldct-denoising-task-lite:0.1.0,sha256:c480902a2e1904102cc9295edbe66dfabe4bacec1cddde2ab0c968b2b1450b20,cb7ac38cb210bd983daf5da14e26a6dcfecc043d19045d364206524260855f18,false,built_verified
|
| 31 |
+
30,enhancement,ldct-denoising-task,ldct-denoising-task,standard,automedbench-full/cell-enhancement-ldct-denoising-task-standard:0.1.0,sha256:96d10ffbc8fee4446554cf17bd3ddd5af6dad1f754b72c39fe725471ff8b21d2,cb7ac38cb210bd983daf5da14e26a6dcfecc043d19045d364206524260855f18,false,built_verified
|
| 32 |
+
31,enhancement,lidc-idri-denoising-task,lidc-idri-denoising-task,lite,automedbench-full/cell-enhancement-lidc-idri-denoising-task-lite:0.1.0,sha256:0c8b4c03d26c8872fc42f881138679e5cf21eb2965be82c81e87744784783b57,514df0777da80a853227f283dc248c0be71964cc3719c526feb56889febde85d,false,built_verified
|
| 33 |
+
32,enhancement,lidc-idri-denoising-task,lidc-idri-denoising-task,standard,automedbench-full/cell-enhancement-lidc-idri-denoising-task-standard:0.1.0,sha256:fec8c634d24f07cefe6287218c46c58d9545578b22cf8c3f832cfdbcef641be9,514df0777da80a853227f283dc248c0be71964cc3719c526feb56889febde85d,false,built_verified
|
| 34 |
+
33,enhancement,deeplesion-denoising-task,deeplesion-denoising-task,lite,automedbench-full/cell-enhancement-deeplesion-denoising-task-lite:0.1.0,sha256:f41cac6211e41b0b1ee5054e96eedc655d952c45a6458c727715654849415828,d7787abb175cffaabf2dced77457d3914deb831e18cbf8f2de5fb02af8d0f823,false,built_verified
|
| 35 |
+
34,enhancement,deeplesion-denoising-task,deeplesion-denoising-task,standard,automedbench-full/cell-enhancement-deeplesion-denoising-task-standard:0.1.0,sha256:2b7bd918a7206ce636dff6e5ba054150b11f5b406b571fbffae8d53e8792cb3e,d7787abb175cffaabf2dced77457d3914deb831e18cbf8f2de5fb02af8d0f823,false,built_verified
|
| 36 |
+
35,enhancement,mri-sr-task,mri-sr-task,lite,automedbench-full/cell-enhancement-mri-sr-task-lite:0.1.0,sha256:38fb3fb3ba548029c0fa56397c37f51bd11f6bbf53a782283831374c0f08b639,47258ec3b0b82b4f5a25662abd00c4345cb3bf90f7c30179110d719a2cd85ba3,false,built_verified
|
| 37 |
+
36,enhancement,mri-sr-task,mri-sr-task,standard,automedbench-full/cell-enhancement-mri-sr-task-standard:0.1.0,sha256:479d5cb6839f5203db83b1dd36d6b0a371d7b7a777b8e8847990b6db1dfc5d76,47258ec3b0b82b4f5a25662abd00c4345cb3bf90f7c30179110d719a2cd85ba3,false,built_verified
|
| 38 |
+
37,enhancement,brats-t1c-sr-task,brats-t1c-sr-task,lite,automedbench-full/cell-enhancement-brats-t1c-sr-task-lite:0.1.0,sha256:30e99825c349e0b0cd3f4189a234e210de4703070b1e3c1c2254b3b73c32ec4d,e8226e6949e8436415e06e48a125b726884590f8eee56e26795f4fbe05a4cc75,false,built_verified
|
| 39 |
+
38,enhancement,brats-t1c-sr-task,brats-t1c-sr-task,standard,automedbench-full/cell-enhancement-brats-t1c-sr-task-standard:0.1.0,sha256:4221f6fb9b4de246e47f8fe52cde7a8d29b825b0c39f8777369cd0d0e052a0ff,e8226e6949e8436415e06e48a125b726884590f8eee56e26795f4fbe05a4cc75,false,built_verified
|
| 40 |
+
39,enhancement,ixi-t1-sr-task,ixi-t1-sr-task,lite,automedbench-full/cell-enhancement-ixi-t1-sr-task-lite:0.1.0,sha256:8623160314a8855325d6918e2aef5784b8b6b44b95d285b18f920d245c83d75e,2e8e8927e9a813b399dd17d19dea7b100ea40a0d8bf10e4fdcdea33ce7c3332b,false,built_verified
|
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93,synthetic,synthetic-msdpancreas-ctsr,msd-pancreas-ctsr-task,lite,automedbench-full/cell-synthetic-msd-pancreas-ctsr-task-lite:0.1.0,sha256:6b742b19451186a4928defcd4367524131cb10f300f3c365f8792b13913dafaa,e2cfcfbeb383b8790286568c3e957a91e2041e9a0841d99a79820423c8355bfd,false,built_verified
|
| 95 |
+
94,synthetic,synthetic-msdpancreas-ctsr,msd-pancreas-ctsr-task,standard,automedbench-full/cell-synthetic-msd-pancreas-ctsr-task-standard:0.1.0,sha256:ac781dfb0e2268703b8f5f30822792f5d794754e1ce6e0ec897952f78e9cf7c6,e2cfcfbeb383b8790286568c3e957a91e2041e9a0841d99a79820423c8355bfd,false,built_verified
|
| 96 |
+
95,synthetic,synthetic-totalseg-ctsr,totalsegmentator-ctsr-task,lite,automedbench-full/cell-synthetic-totalsegmentator-ctsr-task-lite:0.1.0,sha256:99a7bb5e50e0805fa1172b91313bb3aa9ad2e261e40b94cefc1cfeddd7aa6c27,8dbc8f6d62a5d0d4e9b88ab804125c81a075e0942c5645d21705c1af31be4d91,false,built_verified
|
| 97 |
+
96,synthetic,synthetic-totalseg-ctsr,totalsegmentator-ctsr-task,standard,automedbench-full/cell-synthetic-totalsegmentator-ctsr-task-standard:0.1.0,sha256:8a6ab9999139fd1f469d0667ae0ebe51e8846a90ee3e604197d9b39b37db5649,8dbc8f6d62a5d0d4e9b88ab804125c81a075e0942c5645d21705c1af31be4d91,false,built_verified
|
manifests/cell_verification.csv
ADDED
|
@@ -0,0 +1,97 @@
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| 1 |
+
combination_index,track,evaluator_task_id,tier,image_tag,image_id,model,turns,elapsed_s,input_tokens,output_tokens,stopped_before_stage,status
|
| 2 |
+
1,segmentation,kidney-seg-task,lite,automedbench-full/cell-segmentation-kidney-seg-task-lite:0.1.0,sha256:05b252d47d86eaa9c642c7e1a1c1cec68f525a2d071591e4fd1b799fcc471b57,openai/openai/gpt-5.5,3,41.173,10446,2117,s3,s1_s2_verified
|
| 3 |
+
2,segmentation,kidney-seg-task,standard,automedbench-full/cell-segmentation-kidney-seg-task-standard:0.1.0,sha256:7bfa4547d98be063664566efed35f4e15860e15327f7ec0413be93f9164862ce,openai/openai/gpt-5.5,3,44.306,8866,2374,s3,s1_s2_verified
|
| 4 |
+
3,segmentation,pancreas-seg-task,lite,automedbench-full/cell-segmentation-pancreas-seg-task-lite:0.1.0,sha256:c75551ef11fd0b066f123b766f817942ee9b288f1e5ea00120bae03449de641e,openai/openai/gpt-5.5,3,29.902,9740,1918,s3,s1_s2_verified
|
| 5 |
+
4,segmentation,pancreas-seg-task,standard,automedbench-full/cell-segmentation-pancreas-seg-task-standard:0.1.0,sha256:fd68f369f52d995fb3e70ddfe7e2490a5580c8d43d3199103ae5aee9aa193060,openai/openai/gpt-5.5,3,45.36,16944,3036,s3,s1_s2_verified
|
| 6 |
+
5,segmentation,pancreas-oar-seg-task,lite,automedbench-full/cell-segmentation-pancreas-oar-seg-task-lite:0.1.0,sha256:46a8d1fc6a54e6d3de21780ce887882cf6b07059ab05a3e3c1c19d2ce848443c,openai/openai/gpt-5.5,3,57.988,17489,2813,s3,s1_s2_verified
|
| 7 |
+
6,segmentation,pancreas-oar-seg-task,standard,automedbench-full/cell-segmentation-pancreas-oar-seg-task-standard:0.1.0,sha256:f46e4826740c097ef59952b5af1702ad9ec36dcd1f8def5ae52d65df9133fe01,openai/openai/gpt-5.5,3,23.896,13455,1567,s3,s1_s2_verified
|
| 8 |
+
7,segmentation,liver-seg-task,lite,automedbench-full/cell-segmentation-liver-seg-task-lite:0.1.0,sha256:731dce1cf740a32692514015277d26441d1aadfde3ec9c686c663c1cabac4dfd,openai/openai/gpt-5.5,3,51.376,8411,1888,s3,s1_s2_verified
|
| 9 |
+
8,segmentation,liver-seg-task,standard,automedbench-full/cell-segmentation-liver-seg-task-standard:0.1.0,sha256:72738ef1f06d6d86b4cdbe1968625c996495c3c3685972bb96d5fbca8d7553b2,openai/openai/gpt-5.5,3,34.822,10689,2506,s3,s1_s2_verified
|
| 10 |
+
9,segmentation,aeropath-seg-task,lite,automedbench-full/cell-segmentation-aeropath-seg-task-lite:0.1.0,sha256:8078390a79d79bcd396a2bda9bf166413e016865de5cc3df52db96b8bf792b68,openai/openai/gpt-5.5,3,49.146,17184,3170,s3,s1_s2_verified
|
| 11 |
+
10,segmentation,aeropath-seg-task,standard,automedbench-full/cell-segmentation-aeropath-seg-task-standard:0.1.0,sha256:6000e7218365b3b999701ba09659b18ea714336b8891039f240b55e8d35db45f,openai/openai/gpt-5.5,3,32.575,13062,2176,s3,s1_s2_verified
|
| 12 |
+
11,segmentation,tsg-multiorgan-seg-task,lite,automedbench-full/cell-segmentation-tsg-multiorgan-seg-task-lite:0.1.0,sha256:4f13044db234c89ff1d4fbb19d22cd7b634564d4dbef8a1a808a92b308368a38,openai/openai/gpt-5.5,3,18.036,11717,1216,s3,s1_s2_verified
|
| 13 |
+
12,segmentation,tsg-multiorgan-seg-task,standard,automedbench-full/cell-segmentation-tsg-multiorgan-seg-task-standard:0.1.0,sha256:d61987eb48bb9d2e25b6cb00e1c04baf4d70d7b4bbcf4eba5e0f612777f89d7a,openai/openai/gpt-5.5,3,26.69,11386,1432,s3,s1_s2_verified
|
| 14 |
+
13,segmentation,colon-seg-task,lite,automedbench-full/cell-segmentation-colon-seg-task-lite:0.1.0,sha256:9885556f522740f931875118cd4b1fddb937878b28743cc94bfa96ac71b9c8ea,openai/openai/gpt-5.5,3,46.05,11573,2325,s3,s1_s2_verified
|
| 15 |
+
14,segmentation,colon-seg-task,standard,automedbench-full/cell-segmentation-colon-seg-task-standard:0.1.0,sha256:6afb0f86b785398e841101f17f47072f3e559d19311e10435c4f50a38184e715,openai/openai/gpt-5.5,3,51.283,15790,3555,s3,s1_s2_verified
|
| 16 |
+
15,segmentation,hepaticvessel-seg-task,lite,automedbench-full/cell-segmentation-hepaticvessel-seg-task-lite:0.1.0,sha256:87b25d99018fe78db4a75a2288d972acc2a3f793d5b44a7ffee2d52b002a7a89,openai/openai/gpt-5.5,3,37.009,9727,2192,s3,s1_s2_verified
|
| 17 |
+
16,segmentation,hepaticvessel-seg-task,standard,automedbench-full/cell-segmentation-hepaticvessel-seg-task-standard:0.1.0,sha256:ccb0b7cbf8ee6d7e218a72a91bf0113d63d47e75933886052403151410134eb6,openai/openai/gpt-5.5,3,40.702,11597,2512,s3,s1_s2_verified
|
| 18 |
+
17,segmentation,spleen-seg-task,lite,automedbench-full/cell-segmentation-spleen-seg-task-lite:0.1.0,sha256:fbfacf3fe93a820387eddb87b2e6b3372f10e224152860aabdbb11e455da1fae,openai/openai/gpt-5.5,3,63.223,9833,2315,s3,s1_s2_verified
|
| 19 |
+
18,segmentation,spleen-seg-task,standard,automedbench-full/cell-segmentation-spleen-seg-task-standard:0.1.0,sha256:e97ffaa77982fd29fc153420315d8b5f72ba8827fc3f97276893dbb1a01d2d36,openai/openai/gpt-5.5,3,38.892,9964,2491,s3,s1_s2_verified
|
| 20 |
+
19,segmentation,feta-seg-task,lite,automedbench-full/cell-segmentation-feta-seg-task-lite:0.1.0,sha256:98919b3742f67f4db001e4b50676d53d8cb00a8c5a727e9e6e3c86888a57e94a,openai/openai/gpt-5.5,3,52.457,13498,3746,s3,s1_s2_verified
|
| 21 |
+
20,segmentation,feta-seg-task,standard,automedbench-full/cell-segmentation-feta-seg-task-standard:0.1.0,sha256:0a5f84432d67fdd86119eb82224d095f1ea13d8a159a50cb67e63554f4c11ce9,openai/openai/gpt-5.5,3,31.474,11398,1935,s3,s1_s2_verified
|
| 22 |
+
21,segmentation,panther-t1-seg-task,lite,automedbench-full/cell-segmentation-panther-t1-seg-task-lite:0.1.0,sha256:3f15e665d4cfde2e12a5849395871355929e47a8282c79c62015db7121fe4542,openai/openai/gpt-5.5,3,61.726,15635,4155,s3,s1_s2_verified
|
| 23 |
+
22,segmentation,panther-t1-seg-task,standard,automedbench-full/cell-segmentation-panther-t1-seg-task-standard:0.1.0,sha256:b7dbc603eb157b7eca789eb3e0e86041caabb62efd65590a6844fedf2472304d,openai/openai/gpt-5.5,3,54.665,12564,3804,s3,s1_s2_verified
|
| 24 |
+
23,segmentation,panther-t2-seg-task,lite,automedbench-full/cell-segmentation-panther-t2-seg-task-lite:0.1.0,sha256:4be0ffe4a878c0d2e12fa64cc47e64d9cedef0fed94b70688565ed09cec5c10c,openai/openai/gpt-5.5,3,53.724,16347,2183,s3,s1_s2_verified
|
| 25 |
+
24,segmentation,panther-t2-seg-task,standard,automedbench-full/cell-segmentation-panther-t2-seg-task-standard:0.1.0,sha256:a9d2c9f0aa61f4030ab831f65b34e100f130ee8271a5c5845face4a54b3f9951,openai/openai/gpt-5.5,3,32.598,10336,2109,s3,s1_s2_verified
|
| 26 |
+
25,segmentation,heart-seg-task,lite,automedbench-full/cell-segmentation-heart-seg-task-lite:0.1.0,sha256:91ed22656a681d03b21f86ce1d355f221298affca41fe295f3201b0ea36203ad,openai/openai/gpt-5.5,3,48.554,9027,1713,s3,s1_s2_verified
|
| 27 |
+
26,segmentation,heart-seg-task,standard,automedbench-full/cell-segmentation-heart-seg-task-standard:0.1.0,sha256:766a0948bf8289813df8f03b7f74fe951c653b29ef5efe722355ab4a8940ebba,openai/openai/gpt-5.5,3,45.942,8795,2345,s3,s1_s2_verified
|
| 28 |
+
27,segmentation,prostate-seg-task,lite,automedbench-full/cell-segmentation-prostate-seg-task-lite:0.1.0,sha256:b708e6d89ab494a06a9c248d048b654479b8430e73af0daa1621b36990bd9f16,openai/openai/gpt-5.5,3,18.804,9454,1340,s3,s1_s2_verified
|
| 29 |
+
28,segmentation,prostate-seg-task,standard,automedbench-full/cell-segmentation-prostate-seg-task-standard:0.1.0,sha256:286a7ee554961cfd408894a6fe3b3d22873deb756e461bd3359c44b6b54719bc,openai/openai/gpt-5.5,3,36.176,9670,2233,s3,s1_s2_verified
|
| 30 |
+
29,enhancement,ldct-denoising-task,lite,automedbench-full/cell-enhancement-ldct-denoising-task-lite:0.1.0,sha256:c480902a2e1904102cc9295edbe66dfabe4bacec1cddde2ab0c968b2b1450b20,openai/openai/gpt-5.5,3,48.365,12510,2271,s3,s1_s2_verified
|
| 31 |
+
30,enhancement,ldct-denoising-task,standard,automedbench-full/cell-enhancement-ldct-denoising-task-standard:0.1.0,sha256:96d10ffbc8fee4446554cf17bd3ddd5af6dad1f754b72c39fe725471ff8b21d2,openai/openai/gpt-5.5,3,47.708,12304,3352,s3,s1_s2_verified
|
| 32 |
+
31,enhancement,lidc-idri-denoising-task,lite,automedbench-full/cell-enhancement-lidc-idri-denoising-task-lite:0.1.0,sha256:0c8b4c03d26c8872fc42f881138679e5cf21eb2965be82c81e87744784783b57,openai/openai/gpt-5.5,3,45.054,8760,2973,s3,s1_s2_verified
|
| 33 |
+
32,enhancement,lidc-idri-denoising-task,standard,automedbench-full/cell-enhancement-lidc-idri-denoising-task-standard:0.1.0,sha256:fec8c634d24f07cefe6287218c46c58d9545578b22cf8c3f832cfdbcef641be9,openai/openai/gpt-5.5,3,53.879,9791,2405,s3,s1_s2_verified
|
| 34 |
+
33,enhancement,deeplesion-denoising-task,lite,automedbench-full/cell-enhancement-deeplesion-denoising-task-lite:0.1.0,sha256:f41cac6211e41b0b1ee5054e96eedc655d952c45a6458c727715654849415828,openai/openai/gpt-5.5,3,50.976,9410,3139,s3,s1_s2_verified
|
| 35 |
+
34,enhancement,deeplesion-denoising-task,standard,automedbench-full/cell-enhancement-deeplesion-denoising-task-standard:0.1.0,sha256:2b7bd918a7206ce636dff6e5ba054150b11f5b406b571fbffae8d53e8792cb3e,openai/openai/gpt-5.5,3,46.027,7697,2572,s3,s1_s2_verified
|
| 36 |
+
35,enhancement,mri-sr-task,lite,automedbench-full/cell-enhancement-mri-sr-task-lite:0.1.0,sha256:38fb3fb3ba548029c0fa56397c37f51bd11f6bbf53a782283831374c0f08b639,openai/openai/gpt-5.5,3,61.614,17735,2776,s3,s1_s2_verified
|
| 37 |
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36,enhancement,mri-sr-task,standard,automedbench-full/cell-enhancement-mri-sr-task-standard:0.1.0,sha256:479d5cb6839f5203db83b1dd36d6b0a371d7b7a777b8e8847990b6db1dfc5d76,openai/openai/gpt-5.5,3,63.342,15504,4417,s3,s1_s2_verified
|
| 38 |
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37,enhancement,brats-t1c-sr-task,lite,automedbench-full/cell-enhancement-brats-t1c-sr-task-lite:0.1.0,sha256:30e99825c349e0b0cd3f4189a234e210de4703070b1e3c1c2254b3b73c32ec4d,openai/openai/gpt-5.5,3,56.971,14664,2629,s3,s1_s2_verified
|
| 39 |
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38,enhancement,brats-t1c-sr-task,standard,automedbench-full/cell-enhancement-brats-t1c-sr-task-standard:0.1.0,sha256:4221f6fb9b4de246e47f8fe52cde7a8d29b825b0c39f8777369cd0d0e052a0ff,openai/openai/gpt-5.5,3,31.897,7706,1802,s3,s1_s2_verified
|
| 40 |
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39,enhancement,ixi-t1-sr-task,lite,automedbench-full/cell-enhancement-ixi-t1-sr-task-lite:0.1.0,sha256:8623160314a8855325d6918e2aef5784b8b6b44b95d285b18f920d245c83d75e,openai/openai/gpt-5.5,3,31.408,8525,2200,s3,s1_s2_verified
|
| 41 |
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40,enhancement,ixi-t1-sr-task,standard,automedbench-full/cell-enhancement-ixi-t1-sr-task-standard:0.1.0,sha256:3c7d9b0f7ac828a4fb6889514f860a882ff5707598ab1cb05e678aff6a79541c,openai/openai/gpt-5.5,3,41.862,7918,2511,s3,s1_s2_verified
|
| 42 |
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41,enhancement,nih-cxr-sr-task,lite,automedbench-full/cell-enhancement-nih-cxr-sr-task-lite:0.1.0,sha256:4aba6afa58876362ab5f3300a85a7cb35ca64182bcbb179305f0a152547d9b59,openai/openai/gpt-5.5,3,52.529,9034,2637,s3,s1_s2_verified
|
| 43 |
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42,enhancement,nih-cxr-sr-task,standard,automedbench-full/cell-enhancement-nih-cxr-sr-task-standard:0.1.0,sha256:3c6862384f7085226109748d94f2fc66b5aa7cd6dd25a7b975a1c8b588910a1b,openai/openai/gpt-5.5,3,58.893,13379,4263,s3,s1_s2_verified
|
| 44 |
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43,vqa,pathvqa-task,lite,automedbench-full/cell-vqa-pathvqa-task-lite:0.1.0,sha256:8b82531b80421b88968460cad6af2c489b7fa6ebd51015a45df20d4e21fb22bf,openai/openai/gpt-5.5,2,34.295,16074,2625,s3,s1_s2_verified
|
| 45 |
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44,vqa,pathvqa-task,standard,automedbench-full/cell-vqa-pathvqa-task-standard:0.1.0,sha256:95eb21b09c978337bce1b5e713140b30713ab6b065238d96ae5d55877e75bc14,openai/openai/gpt-5.5,2,50.18,13408,4234,s3,s1_s2_verified
|
| 46 |
+
45,vqa,vqa-rad-task,lite,automedbench-full/cell-vqa-vqa-rad-task-lite:0.1.0,sha256:697f3494802ca0672f66ab8b3673b1e28cc0d0665e26d27c5fc17f99361e76d7,openai/openai/gpt-5.5,2,29.304,14769,2356,s3,s1_s2_verified
|
| 47 |
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46,vqa,vqa-rad-task,standard,automedbench-full/cell-vqa-vqa-rad-task-standard:0.1.0,sha256:379025877844fbefa4897fb7105891f7281ea445008cb78058885e34b54f9705,openai/openai/gpt-5.5,3,84.098,28506,8046,s3,s1_s2_verified
|
| 48 |
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47,vqa,medframeqa-task,lite,automedbench-full/cell-vqa-medframeqa-task-lite:0.1.0,sha256:ace9d741d01ab54911fb5451c58156b0dd04561d6030e911d1fc9a6d38479ac4,openai/openai/gpt-5.5,2,29.551,14635,2420,s3,s1_s2_verified
|
| 49 |
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48,vqa,medframeqa-task,standard,automedbench-full/cell-vqa-medframeqa-task-standard:0.1.0,sha256:b8e104e60d42070da02849272fb524670279781c50884543e945a88cad6a4f08,openai/openai/gpt-5.5,2,50.532,13093,3875,s3,s1_s2_verified
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| 50 |
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49,vqa,slake-task,lite,automedbench-full/cell-vqa-slake-task-lite:0.1.0,sha256:a4e40b25e332c9ca7e3bc49efc59bc78506a6c0d8ab8b54ab9478d9d4de852d5,openai/openai/gpt-5.5,2,32.954,14528,2655,s3,s1_s2_verified
|
| 51 |
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50,vqa,slake-task,standard,automedbench-full/cell-vqa-slake-task-standard:0.1.0,sha256:79c9895588962dddd2ff2c167a9db7e53f2eb8b226b9fcefb7b24298d4786943,openai/openai/gpt-5.5,2,59.08,15126,4912,s3,s1_s2_verified
|
| 52 |
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51,vqa,medxpertqa-mm-task,lite,automedbench-full/cell-vqa-medxpertqa-mm-task-lite:0.1.0,sha256:70f56488a821d55eb4642673afe465998067abdbeed3689de794c24d1a24a484,openai/openai/gpt-5.5,2,37.047,14349,2734,s3,s1_s2_verified
|
| 53 |
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52,vqa,medxpertqa-mm-task,standard,automedbench-full/cell-vqa-medxpertqa-mm-task-standard:0.1.0,sha256:623c40bc2b0cf8cffdc1043ecf0a78a07328f7be09c5ea1506e7be78640d0cf6,openai/openai/gpt-5.5,2,51.316,13236,4101,s3,s1_s2_verified
|
| 54 |
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53,vqa,vqa-kvasir-task,lite,automedbench-full/cell-vqa-vqa-kvasir-task-lite:0.1.0,sha256:5e27ed5a08d82634ee0602016ddc7be408d65a40fec675dc0404ff8e3a5d1b36,openai/openai/gpt-5.5,3,37.098,21015,3052,s3,s1_s2_verified
|
| 55 |
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54,vqa,vqa-kvasir-task,standard,automedbench-full/cell-vqa-vqa-kvasir-task-standard:0.1.0,sha256:d5645e9287605647fab4a8e83def6b0827c0d137fb384a2e279d691e5e2353db,openai/openai/gpt-5.5,3,66.531,21726,6674,s3,s1_s2_verified
|
| 56 |
+
55,vqa,vqa-omnimedvqa-task,lite,automedbench-full/cell-vqa-vqa-omnimedvqa-task-lite:0.1.0,sha256:3b30f72a383e443231487f61e56718660400a8f6c1efb821c47e9805a817bf89,openai/openai/gpt-5.5,2,32.351,13440,2751,s3,s1_s2_verified
|
| 57 |
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56,vqa,vqa-omnimedvqa-task,standard,automedbench-full/cell-vqa-vqa-omnimedvqa-task-standard:0.1.0,sha256:b6fc306733516196b68e88425a2fefc924c74933231794a383971686c4b98562,openai/openai/gpt-5.5,3,49.816,21138,3990,s3,s1_s2_verified
|
| 58 |
+
57,vqa,vqa-pmc-vqa-task,lite,automedbench-full/cell-vqa-vqa-pmc-vqa-task-lite:0.1.0,sha256:cfc3d9b38f74f35e8c64fe395b374d60236fde149088b1a866b4b418c0d6d7a5,openai/openai/gpt-5.5,2,25.914,13970,2271,s3,s1_s2_verified
|
| 59 |
+
58,vqa,vqa-pmc-vqa-task,standard,automedbench-full/cell-vqa-vqa-pmc-vqa-task-standard:0.1.0,sha256:ab87977e19ab8b66f6461b85a13929015f822026496e2f56278e35c520e47c0c,openai/openai/gpt-5.5,2,49.087,11463,4169,s3,s1_s2_verified
|
| 60 |
+
59,vqa,vqa-mmmu-medical-task,lite,automedbench-full/cell-vqa-vqa-mmmu-medical-task-lite:0.1.0,sha256:2a8cac1ddbedc43d2c1f812c7bc0bbf21c91037209ba57f6009e89159c9f6e32,openai/openai/gpt-5.5,3,34.259,20329,2618,s3,s1_s2_verified
|
| 61 |
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60,vqa,vqa-mmmu-medical-task,standard,automedbench-full/cell-vqa-vqa-mmmu-medical-task-standard:0.1.0,sha256:0ad7b61835b1d7a9bd295319b54375b7a40c05f00d25aac63d2ee872db471dc7,openai/openai/gpt-5.5,2,52.986,11628,3980,s3,s1_s2_verified
|
| 62 |
+
61,report,mimic-cxr-report-task,lite,automedbench-full/cell-report-mimic-cxr-report-task-lite:0.1.0,sha256:e48a0117a61c9a81a887b0b9b6e6015690f6fad166b6b32692cc79a1697f4513,openai/openai/gpt-5.5,3,19.231,8581,1323,s3,s1_s2_verified
|
| 63 |
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62,report,mimic-cxr-report-task,standard,automedbench-full/cell-report-mimic-cxr-report-task-standard:0.1.0,sha256:d34c6d01bd9ac535417e4b8148331458e5821b4b50cb329ce1a189bde6d6f2a0,openai/openai/gpt-5.5,3,14.831,5933,975,s3,s1_s2_verified
|
| 64 |
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63,report,iu-xray-report-task,lite,automedbench-full/cell-report-iu-xray-report-task-lite:0.1.0,sha256:77d68ea21c8be645981bdcb49247e24d24c956da31aa553130aba1103c3292ed,openai/openai/gpt-5.5,3,24.243,3395,1637,s3,s1_s2_verified
|
| 65 |
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64,report,iu-xray-report-task,standard,automedbench-full/cell-report-iu-xray-report-task-standard:0.1.0,sha256:4b2a4bf60246960896b23f2399a7488beed1366eecc7ddf901fc7e67a5b53acf,openai/openai/gpt-5.5,3,24.261,4289,1716,s3,s1_s2_verified
|
| 66 |
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65,report,chexpert-plus-cxr-task,lite,automedbench-full/cell-report-chexpert-plus-cxr-task-lite:0.1.0,sha256:a6769cb85a9c2dd0dd8141e978934d1887d5dd4d97cd7e9a560bbeed097ff8f0,openai/openai/gpt-5.5,3,15.325,6104,942,s3,s1_s2_verified
|
| 67 |
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66,report,chexpert-plus-cxr-task,standard,automedbench-full/cell-report-chexpert-plus-cxr-task-standard:0.1.0,sha256:ba0f55de68d07cad585c3a9b0e32c284ba0d297e5ca6d93a490025e87e40192d,openai/openai/gpt-5.5,3,13.125,5265,793,s3,s1_s2_verified
|
| 68 |
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67,report,pathology-caption-100-task,lite,automedbench-full/cell-report-pathology-caption-100-task-lite:0.1.0,sha256:835b9ee69f013e37979d01491d517b71ab60365ebfe2e4bcf1ee0316b606762a,openai/openai/gpt-5.5,3,13.508,3276,848,s3,s1_s2_verified
|
| 69 |
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68,report,pathology-caption-100-task,standard,automedbench-full/cell-report-pathology-caption-100-task-standard:0.1.0,sha256:da107c64edbcf5761ef36a5f9d72057884ea49c2f394fcc668c84d92a142d541,openai/openai/gpt-5.5,3,13.192,2987,825,s3,s1_s2_verified
|
| 70 |
+
69,report,pathology-caption-500-task,lite,automedbench-full/cell-report-pathology-caption-500-task-lite:0.1.0,sha256:5808fb01de64174e30ecda9b0a47f502264cb59112c982b2190772d9f8a4a988,openai/openai/gpt-5.5,3,20.186,4188,1453,s3,s1_s2_verified
|
| 71 |
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70,report,pathology-caption-500-task,standard,automedbench-full/cell-report-pathology-caption-500-task-standard:0.1.0,sha256:7db78b3087a1e8c80d0ef4e3bfed71e45d14dc15ebb44460106f522035137c4f,openai/openai/gpt-5.5,3,26.843,2899,1459,s3,s1_s2_verified
|
| 72 |
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71,detection,vindr-cxr-det-task,lite,automedbench-full/cell-detection-vindr-cxr-det-task-lite:0.1.0,sha256:e7b43ab642109e815526c3bf588b93d13047a1a30515a9d7933e87ebc8d168a9,openai/openai/gpt-5.5,3,41.443,15215,2956,s3,s1_s2_verified
|
| 73 |
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72,detection,vindr-cxr-det-task,standard,automedbench-full/cell-detection-vindr-cxr-det-task-standard:0.1.0,sha256:8cce5ac710ac718ef73ad91769b9afec5ce80e27ef1401b68a3149d46f9790a2,openai/openai/gpt-5.5,3,43.481,14014,2502,s3,s1_s2_verified
|
| 74 |
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73,detection,bccd-det-task,lite,automedbench-full/cell-detection-bccd-det-task-lite:0.1.0,sha256:5df3844902712f640ee0898299e37b4c698f4a7d8ebe9bf23ed3c112fa85e950,openai/openai/gpt-5.5,3,32.73,11907,2323,s3,s1_s2_verified
|
| 75 |
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74,detection,bccd-det-task,standard,automedbench-full/cell-detection-bccd-det-task-standard:0.1.0,sha256:797dc663f39dc5c2b3b974ed34fdb7f6bf3a7b906dc7ec0d3d966cb4c0dfadaf,openai/openai/gpt-5.5,3,82.833,21281,7378,s3,s1_s2_verified
|
| 76 |
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75,detection,dentex-det-task,lite,automedbench-full/cell-detection-dentex-det-task-lite:0.1.0,sha256:cccd5c7d31ef890706538dcf36f7806d77d13f8c9c408a99e664027c64e120ff,openai/openai/gpt-5.5,3,29.829,12694,1919,s3,s1_s2_verified
|
| 77 |
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76,detection,dentex-det-task,standard,automedbench-full/cell-detection-dentex-det-task-standard:0.1.0,sha256:dd9fbf3a817ac5ae7198bef486b7295c5ac11d199f0b615b2262fe8efdeb1a7f,openai/openai/gpt-5.5,3,44.717,11736,2941,s3,s1_s2_verified
|
| 78 |
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77,detection,grazpedwri-det-task,lite,automedbench-full/cell-detection-grazpedwri-det-task-lite:0.1.0,sha256:59dea4432206af33f61525c08a807b279b56c3c11f90ec187e2a4928917cff6f,openai/openai/gpt-5.5,2,33.101,9760,2574,s3,s1_s2_verified
|
| 79 |
+
78,detection,grazpedwri-det-task,standard,automedbench-full/cell-detection-grazpedwri-det-task-standard:0.1.0,sha256:c30b2f9ef32326c33c06f399c34cce85bbae375b2826de3faf4cd5b47e1efbb0,openai/openai/gpt-5.5,3,62.095,16510,4751,s3,s1_s2_verified
|
| 80 |
+
79,classification,braintumor-cls-task,lite,automedbench-full/cell-classification-braintumor-cls-task-lite:0.1.0,sha256:4ba84490d8142ef1c086971f7d6f18a025b2185edba1aafdc00f8cd245cd83a1,openai/openai/gpt-5.5,3,54.586,8427,2663,s3,s1_s2_verified
|
| 81 |
+
80,classification,braintumor-cls-task,standard,automedbench-full/cell-classification-braintumor-cls-task-standard:0.1.0,sha256:5fbae86635c919e149c942637eb799544b459ab3d6273c6f3a9859fb4923987b,openai/openai/gpt-5.5,3,46.472,9125,2479,s3,s1_s2_verified
|
| 82 |
+
81,classification,crc-histology-cls-task,lite,automedbench-full/cell-classification-crc-histology-cls-task-lite:0.1.0,sha256:b1882af23d0cc56d0da84d833dcf77334b67195c4c253525d808fa698a4e7dcc,openai/openai/gpt-5.5,3,59.786,8722,3249,s3,s1_s2_verified
|
| 83 |
+
82,classification,crc-histology-cls-task,standard,automedbench-full/cell-classification-crc-histology-cls-task-standard:0.1.0,sha256:18c6c76d141d37b9c8dd430e2a3cd214fc799bea2a3ab9b160533fd1c48f97f1,openai/openai/gpt-5.5,3,25.952,7410,1350,s3,s1_s2_verified
|
| 84 |
+
83,classification,patchcamelyon-cls-task,lite,automedbench-full/cell-classification-patchcamelyon-cls-task-lite:0.1.0,sha256:1a2fcd4f5f564e251108b2053d5534af2e62900f15b9479b912666ce0961e1f1,openai/openai/gpt-5.5,3,44.576,7703,1620,s3,s1_s2_verified
|
| 85 |
+
84,classification,patchcamelyon-cls-task,standard,automedbench-full/cell-classification-patchcamelyon-cls-task-standard:0.1.0,sha256:901eba7dc7316995f66794fc1d80bb722f10ba057626ee78a0b6eae726d20c1a,openai/openai/gpt-5.5,3,28.774,7856,1748,s3,s1_s2_verified
|
| 86 |
+
85,classification,chest-xray-pneumonia-cls-task,lite,automedbench-full/cell-classification-chest-xray-pneumonia-cls-task-lite:0.1.0,sha256:58b4d539bbecb58155bd13b1998a11a69c0eceaa861ae40545dea3c4636d1171,openai/openai/gpt-5.5,3,54.093,12094,2960,s3,s1_s2_verified
|
| 87 |
+
86,classification,chest-xray-pneumonia-cls-task,standard,automedbench-full/cell-classification-chest-xray-pneumonia-cls-task-standard:0.1.0,sha256:57e1cee816cd282e496be2e0ce1ff5736d869630e5c9d045113e25d8b43893ec,openai/openai/gpt-5.5,3,27.523,7441,1644,s3,s1_s2_verified
|
| 88 |
+
87,classification,skin-lesion-cls-task,lite,automedbench-full/cell-classification-skin-lesion-cls-task-lite:0.1.0,sha256:535cb11b26e295623ea563db77c3a8f90393f073553686d9b7110309a5c5758e,openai/openai/gpt-5.5,3,49.578,10434,2196,s3,s1_s2_verified
|
| 89 |
+
88,classification,skin-lesion-cls-task,standard,automedbench-full/cell-classification-skin-lesion-cls-task-standard:0.1.0,sha256:6eb7de95e0be85fb1c39ec742f59ea79af77bdcd9000f8fcbc262c5c2fc76240,openai/openai/gpt-5.5,3,26.995,8569,1707,s3,s1_s2_verified
|
| 90 |
+
89,synthetic,synthrad2025-mrct-task,lite,automedbench-full/cell-synthetic-synthrad2025-mrct-task-lite:0.1.0,sha256:b566533d9cd3e14d844580da1e9825398780f83ef042e3d0dbaa09a79111b71d,openai/openai/gpt-5.5,3,49.249,8375,2003,s3,s1_s2_verified
|
| 91 |
+
90,synthetic,synthrad2025-mrct-task,standard,automedbench-full/cell-synthetic-synthrad2025-mrct-task-standard:0.1.0,sha256:a2800aedb24506bb7b63abcd059067ae1127ebb3c069a6cadeda873656b856e3,openai/openai/gpt-5.5,3,44.042,12600,3008,s3,s1_s2_verified
|
| 92 |
+
91,synthetic,ctorg-ctsr-task,lite,automedbench-full/cell-synthetic-ctorg-ctsr-task-lite:0.1.0,sha256:30f8943102bd5c48c2fd2fd3bfe77642e9716e09fc6f2c4faf25019c094ead03,openai/openai/gpt-5.5,3,36.255,9485,2315,s3,s1_s2_verified
|
| 93 |
+
92,synthetic,ctorg-ctsr-task,standard,automedbench-full/cell-synthetic-ctorg-ctsr-task-standard:0.1.0,sha256:ccef3503b3bbbb4b27ace0b4adfd45a13e10b0141a3f0a740a9a69569d1f583b,openai/openai/gpt-5.5,3,22.082,8924,1305,s3,s1_s2_verified
|
| 94 |
+
93,synthetic,msd-pancreas-ctsr-task,lite,automedbench-full/cell-synthetic-msd-pancreas-ctsr-task-lite:0.1.0,sha256:6b742b19451186a4928defcd4367524131cb10f300f3c365f8792b13913dafaa,openai/openai/gpt-5.5,3,45.118,10590,2721,s3,s1_s2_verified
|
| 95 |
+
94,synthetic,msd-pancreas-ctsr-task,standard,automedbench-full/cell-synthetic-msd-pancreas-ctsr-task-standard:0.1.0,sha256:ac781dfb0e2268703b8f5f30822792f5d794754e1ce6e0ec897952f78e9cf7c6,openai/openai/gpt-5.5,3,56.751,11498,2618,s3,s1_s2_verified
|
| 96 |
+
95,synthetic,totalsegmentator-ctsr-task,lite,automedbench-full/cell-synthetic-totalsegmentator-ctsr-task-lite:0.1.0,sha256:99a7bb5e50e0805fa1172b91313bb3aa9ad2e261e40b94cefc1cfeddd7aa6c27,openai/openai/gpt-5.5,3,31.487,7770,1950,s3,s1_s2_verified
|
| 97 |
+
96,synthetic,totalsegmentator-ctsr-task,standard,automedbench-full/cell-synthetic-totalsegmentator-ctsr-task-standard:0.1.0,sha256:8a6ab9999139fd1f469d0667ae0ebe51e8846a90ee3e604197d9b39b37db5649,openai/openai/gpt-5.5,3,29.077,9090,1975,s3,s1_s2_verified
|
manifests/data_policy.csv
ADDED
|
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| 1 |
+
track,website_task_id,evaluator_task_id,data_dir_name,upstream,upstream_url,access,license,policy,size_evidence,staging_ref,release_gate
|
| 2 |
+
segmentation,kidney,kidney-seg-task,Abdomen_Kidney,KiTS19,https://kits19.grand-challenge.org/,public,CC BY-NC-SA 4.0,redistributable,about 200 MB per source case,609c2a8:stage_data.py,Attribution and NC-SA terms required; staging output directory currently mismatches config
|
| 3 |
+
segmentation,pancreas,pancreas-seg-task,Abdomen_Pancreas,PanTS,https://github.com/MrGiovanni/PanTS,public,CC BY-NC-ND 4.0,restricted,about 300 to 346 GB full,609c2a8:stage_data.py,Do not redistribute converted or staged derivatives
|
| 4 |
+
segmentation,pancreas_oar,pancreas-oar-seg-task,Abdomen_Pancreas_OAR,PanTS,https://github.com/MrGiovanni/PanTS,public,CC BY-NC-ND 4.0,restricted,about 300 to 346 GB full,,Do not redistribute converted or staged derivatives
|
| 5 |
+
segmentation,liver,liver-seg-task,Abdomen_Liver,LiTS declared but script uses MSD Task03,https://medicaldecathlon.com/,public,provenance conflict,unknown,MSD mirror archive about 28.9 GB,609c2a8:stage_data.py,Resolve LiTS versus MSD provenance and output directory mismatch
|
| 6 |
+
segmentation,aeropath,aeropath-seg-task,AeroPath,AeroPath,https://zenodo.org/records/10069289,public,CC BY 4.0,redistributable,about 5.04 GB,,Include attribution and license
|
| 7 |
+
segmentation,totalsegmentator,tsg-multiorgan-seg-task,TSG_multi-organ,TotalSegmentator small v2.0.1,https://zenodo.org/records/10047263,public,CC BY 4.0,redistributable,3.24 GB source and 0.933 GB locally staged,,Freeze source version and include attribution
|
| 8 |
+
segmentation,colon,colon-seg-task,MSD_Colon,MSD Task10 Colon,https://medicaldecathlon.com/,public,CC BY-SA 4.0,redistributable,about 6.24 GB,,Include attribution and share-alike license
|
| 9 |
+
segmentation,hepaticvessel,hepaticvessel-seg-task,MSD_HepaticVessel,MSD Task08 HepaticVessel,https://medicaldecathlon.com/,public,CC BY-SA 4.0,redistributable,about 9.35 GB,,Include attribution and share-alike license
|
| 10 |
+
segmentation,spleen,spleen-seg-task,MSD_Spleen,MSD Task09 Spleen,https://medicaldecathlon.com/,public,CC BY-SA 4.0,redistributable,about 1.61 GB,,Include attribution and share-alike license
|
| 11 |
+
segmentation,feta,feta-seg-task,CruzMRI_Feta,FeTA,https://zenodo.org/records/4541606,gated,research and education agreement,restricted,size unavailable anonymously,,Authorized users must acquire data independently
|
| 12 |
+
segmentation,panther_t1,panther-t1-seg-task,PANTHER_Task1,PANTHER,https://zenodo.org/records/15192302,restricted_access,CC BY-NC 4.0 plus access controls,restricted,size unavailable anonymously,609c2a8:eval_seg/stage_panther.py,Authorized users must acquire data independently
|
| 13 |
+
segmentation,panther_t2,panther-t2-seg-task,PANTHER_Task2,PANTHER,https://zenodo.org/records/15192302,restricted_access,CC BY-NC 4.0 plus access controls,restricted,size unavailable anonymously,609c2a8:eval_seg/stage_panther.py,Authorized users must acquire data independently
|
| 14 |
+
segmentation,heart,heart-seg-task,MSD_Heart,MSD Task02 Heart,https://medicaldecathlon.com/,public,CC BY-SA 4.0,redistributable,about 456 MB,,Include attribution and share-alike license
|
| 15 |
+
segmentation,prostate,prostate-seg-task,MSD_Prostate,MSD Task05 Prostate,https://medicaldecathlon.com/,public,CC BY-SA 4.0,redistributable,about 240 MB,,Include attribution and share-alike license
|
| 16 |
+
enhancement,ldct-denoising-task,ldct-denoising-task,LDCT_SimNICT,AAPM Low Dose CT Grand Challenge,https://www.aapm.org/grandchallenge/lowdosect/,public_library,no explicit redistribution grant located,download_required,42 MB locally staged,,Download from upstream; do not embed
|
| 17 |
+
enhancement,lidc-idri-denoising-task,lidc-idri-denoising-task,LIDC_IDRI_Denoising,LIDC-IDRI,https://www.cancerimagingarchive.net/collection/lidc-idri/,public,CC BY 3.0,redistributable,about 136.55 GB full,release_tasks/enhancement/lidc-idri-denoising-task,Release-owned harness; freeze selected cases and include attribution
|
| 18 |
+
enhancement,deeplesion-denoising-task,deeplesion-denoising-task,DeepLesion_Denoising,NIH DeepLesion,https://nihcc.app.box.com/v/DeepLesion,public,no explicit data license confirmed,unknown,size unknown,release_tasks/enhancement/deeplesion-denoising-task,Release-owned harness; redistribution grant remains unresolved
|
| 19 |
+
enhancement,mri-sr-task,mri-sr-task,MRI_SR_SRMRI,fastMRI,https://fastmri.med.nyu.edu/,application_required,agreement prohibits redistribution,restricted,selected size not specified,,Authorized users must acquire data independently
|
| 20 |
+
enhancement,brats-t1c-sr-task,brats-t1c-sr-task,BraTS_T1c_SR,BraTS 2023 GLI,https://www.synapse.org/Synapse:syn51156910/wiki/,controlled,controlled access terms,restricted,size unknown,release_tasks/enhancement/brats-t1c-sr-task,Release-owned harness; authorized users must acquire data independently
|
| 21 |
+
enhancement,ixi-t1-sr-task,ixi-t1-sr-task,IXI_T1_SR,IXI T1,https://brain-development.org/ixi-dataset/,public,CC BY-SA 3.0,redistributable,official T1 size not displayed,release_tasks/enhancement/ixi-t1-sr-task,Release-owned harness; include attribution and share-alike license
|
| 22 |
+
enhancement,nih-cxr-sr-task,nih-cxr-sr-task,NIH_CXR_SR,NIH ChestXray14,https://nihcc.app.box.com/v/ChestXray-NIHCC,public,CC0 in NIH Kaggle distribution,redistributable,about 45.08 GB,release_tasks/enhancement/nih-cxr-sr-task,Release-owned harness; freeze source provenance
|
| 23 |
+
vqa,vqa-pathvqa-task,pathvqa-task,PathVQA,PathVQA,https://huggingface.co/datasets/flaviagiammarino/path-vqa,public,MIT,redistributable,about 785 MB,99c166a:eval_vqa/stage_hf_datasets.py,Include license and source attribution
|
| 24 |
+
vqa,vqa-radvqa-task,vqa-rad-task,VQA_RAD,VQA-RAD,https://huggingface.co/datasets/flaviagiammarino/vqa-rad,public,CC0 1.0,redistributable,about 34.5 MB,99c166a:eval_vqa/stage_hf_datasets.py,Freeze source revision
|
| 25 |
+
vqa,vqa-medframeqa-task,medframeqa-task,MedFrameQA,MedFrameQA,https://huggingface.co/datasets/SuhaoYu1020/MedFrameQA,public,CC BY 4.0,redistributable,about 571 MB,99c166a:eval_vqa/stage_hf_datasets.py,Include attribution
|
| 26 |
+
vqa,vqa-slake-task,slake-task,SLAKE_EN,SLAKE,https://huggingface.co/datasets/BoKelvin/SLAKE,public,CC BY 4.0,redistributable,about 217 MB,99c166a:eval_vqa/stage_hf_datasets.py,Include attribution
|
| 27 |
+
vqa,vqa-medxpertqa-mm-task,medxpertqa-mm-task,MedXpertQA_MM,MedXpertQA,https://huggingface.co/datasets/TsinghuaC3I/MedXpertQA,public,MIT,redistributable,523 MB source and 275 MB locally staged,99c166a:eval_vqa/stage_data.py,Include license and source attribution
|
| 28 |
+
vqa,vqa-kvasir-task,vqa-kvasir-task,KvasirVQA,Kvasir-VQA,https://huggingface.co/datasets/SimulaMet-HOST/Kvasir-VQA,public_permission_required,CC BY-NC 4.0 with benchmark permission condition,restricted,1.55 GB download and about 15.18 GB expanded,release_tasks/vqa/vqa-kvasir-task,Release-owned harness; obtain written benchmark permission
|
| 29 |
+
vqa,vqa-omnimedvqa-task,vqa-omnimedvqa-task,OmniMedVQA,OmniMedVQA,https://huggingface.co/datasets/foreverbeliever/OmniMedVQA,mixed_access,no global license and mixed source terms,restricted,about 10.70 GB repository,release_tasks/vqa/vqa-omnimedvqa-task,Release-owned harness; independently acquire authorized source subsets
|
| 30 |
+
vqa,vqa-pmc-vqa-task,vqa-pmc-vqa-task,PMC_VQA,PMC-VQA,https://huggingface.co/datasets/RadGenome/PMC-VQA,public,CC BY-SA,redistributable,about 21.77 GB,release_tasks/vqa/vqa-pmc-vqa-task,Release-owned harness; include attribution and share-alike license
|
| 31 |
+
vqa,vqa-mmmu-medical-task,vqa-mmmu-medical-task,MMMU_Medical,MMMU medical subsets,https://huggingface.co/datasets/MMMU/MMMU,public,Apache-2.0,redistributable,2.09 GB full repository,release_tasks/vqa/vqa-mmmu-medical-task,Release-owned harness; freeze five medical validation subsets
|
| 32 |
+
report,mimic-cxr-report-task,mimic-cxr-report-task,MIMIC_CXR_Report,MIMIC-CXR,https://physionet.org/content/mimic-cxr/2.1.0/,credentialed_DUA,DUA prohibits sharing,restricted,377110 images full,0fa32bb:eval_report_gen/stage_data.py,Authorized users must acquire data independently
|
| 33 |
+
report,iu-xray-report-task,iu-xray-report-task,IU_Xray_Report,IU Open-i,https://openi.nlm.nih.gov/,public_search,no clear bulk redistribution license located,unknown,size unknown,release_tasks/report/iu-xray-report-task,Release-owned harness; redistribution grant remains unresolved
|
| 34 |
+
report,chexpert-plus-cxr-task,chexpert-plus-cxr-task,CheXpert_Plus_Report,CheXpert Plus,https://aimi.stanford.edu/datasets/chexpert-plus,public_mirror,no license declared by current mirror,unknown,636 MB mirror and 217 MB locally staged,0fa32bb:eval_report_gen/stage_hf_datasets.py,Hold until exact Stanford terms and source revision are recorded
|
| 35 |
+
report,pathology-caption-100-task,pathology-caption-100-task,Pathology_Caption,PathCap,https://huggingface.co/datasets/jamessyx/PathCap,auto_gated,CC BY-NC 2.0 plus click-through,restricted,about 13.7 GB,0fa32bb:eval_report_gen/stage_hf_datasets.py,Missing harness; current staging does not distinguish 100 and 500
|
| 36 |
+
report,pathology-caption-500-task,pathology-caption-500-task,Pathology_Caption,PathCap,https://huggingface.co/datasets/jamessyx/PathCap,auto_gated,CC BY-NC 2.0 plus click-through,restricted,about 13.7 GB,0fa32bb:eval_report_gen/stage_hf_datasets.py,Missing harness; current staging does not distinguish 100 and 500
|
| 37 |
+
detection,detection-cxr-abnormality-vindr,vindr-cxr-det-task,VinDrCXR_Detection100,VinDr-CXR,https://physionet.org/content/vindr-cxr/1.0.0/,credentialed_DUA,PhysioNet Credentialed Health Data License,restricted,size hidden until authorized,07b8328:eval_det2d/scripts/stage_from_kaggle.sh,Authorized users must acquire data independently
|
| 38 |
+
detection,detection-bccd-blood-cell,bccd-det-task,BCCD_Detection100,BCCD,https://github.com/Shenggan/BCCD_Dataset,public,MIT,redistributable,about 4.95 MB mirror,07b8328:eval_det2d/scripts/stage_bccd.py,Include license and source attribution
|
| 39 |
+
detection,detection-dentex-dental-disease,dentex-det-task,DENTEX_Detection100,DENTEX,https://huggingface.co/datasets/ibrahimhamamci/DENTEX,public,CC BY-NC-SA 4.0,redistributable,about 11.84 GB repository,07b8328:eval_det2d/scripts/stage_dentex.py,Include NC-SA terms and attribution
|
| 40 |
+
detection,detection-grazpedwri-wrist-anomaly,grazpedwri-det-task,GRAZPEDWRI_Detection100,GRAZPEDWRI-DX,https://figshare.com/articles/dataset/GRAZPEDWRI-DX/14825193,public,CC BY 4.0,redistributable,16.26 GB full and 24.4 MB locally staged,07b8328:eval_det2d/scripts/stage_grazpedwri.py,Include attribution
|
| 41 |
+
classification,classification-braintumor-mri,braintumor-cls-task,BrainTumorMRI,Brain Tumor MRI,https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset,public,CC BY 4.0,redistributable,about 167.85 MB,,Include attribution and source provenance
|
| 42 |
+
classification,classification-crc-histology,crc-histology-cls-task,CRC_Histology,NCT-CRC-HE-100K,https://zenodo.org/records/1214456,public,CC BY 4.0,redistributable,about 11.7 GB,release_tasks/classification/crc-histology-cls-task,Release-owned harness; freeze 100-case split and include attribution
|
| 43 |
+
classification,classification-pcam-metastasis,patchcamelyon-cls-task,PatchCamelyon,PatchCamelyon,https://github.com/basveeling/pcam,public,CC0,redistributable,about 7.7 GB image archives,release_tasks/classification/patchcamelyon-cls-task,Release-owned harness; freeze 100-case split
|
| 44 |
+
classification,classification-chest-pneumonia,chest-xray-pneumonia-cls-task,ChestXrayPneumonia,Kermany chest X-ray pneumonia,https://data.mendeley.com/datasets/rscbjbr9sj/2,public,CC BY 4.0,redistributable,size not stated concisely,release_tasks/classification/chest-xray-pneumonia-cls-task,Release-owned harness; freeze 100-case split and include attribution
|
| 45 |
+
classification,classification-isic-skin-lesion,skin-lesion-cls-task,SkinLesionISIC,ISIC Archive,https://www.isic-archive.com/,public,per-image licenses not frozen,unknown,6.26 MB locally staged,,Freeze image IDs and their individual licenses before upload
|
| 46 |
+
synthetic,synthetic-synthrad-mrct,synthrad2025-mrct-task,SynthRAD2025_MRCT_HN20,SynthRAD2025,https://zenodo.org/records/15373853,public,CC BY-NC 4.0,redistributable,Task 1 archive about 14.8 GB,b4fe0cb:eval_synthetic/stage_data.py,Include NC terms and attribution
|
| 47 |
+
synthetic,synthetic-ctorg-ctsr,ctorg-ctsr-task,CTORG_CT_SR20,CT-ORG,https://www.cancerimagingarchive.net/collection/ct-org/,public,CC BY 3.0,redistributable,full source size not exposed,b4fe0cb:eval_synthetic/stage_ctsr_data.py,Include attribution and freeze source revision
|
| 48 |
+
synthetic,synthetic-msdpancreas-ctsr,msd-pancreas-ctsr-task,MSD_Pancreas_CT_SR20,MSD Task07 Pancreas,https://medicaldecathlon.com/,public,CC BY-SA 4.0,redistributable,12.3 GB source and 1.472 GB locally staged,b4fe0cb:eval_synthetic/stage_ctsr_data.py,Include attribution and share-alike license
|
| 49 |
+
synthetic,synthetic-totalseg-ctsr,totalsegmentator-ctsr-task,TotalSegmentator_CT_SR20,TotalSegmentator,https://github.com/wasserth/TotalSegmentator,public,CC BY 4.0,redistributable,archive version and size not frozen,b4fe0cb:eval_synthetic/stage_ctsr_data.py,Freeze source version and include attribution
|
manifests/dataset_resolution.csv
ADDED
|
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| 1 |
+
track,website_task_id,evaluator_task_id,data_dir_name,resolution_status,access,policy,upstream,upstream_url,source_ref,local_file_count,local_bytes,layout_sha256,release_gate
|
| 2 |
+
segmentation,kidney,kidney-seg-task,Abdomen_Kidney,acquisition_ready,public,redistributable,KiTS19,https://kits19.grand-challenge.org/,609c2a8:stage_data.py,0,0,,Attribution and NC-SA terms required; staging output directory currently mismatches config
|
| 3 |
+
segmentation,pancreas,pancreas-seg-task,Abdomen_Pancreas,acquisition_ready,public,restricted,PanTS,https://github.com/MrGiovanni/PanTS,609c2a8:stage_data.py,0,0,,Do not redistribute converted or staged derivatives
|
| 4 |
+
segmentation,pancreas_oar,pancreas-oar-seg-task,Abdomen_Pancreas_OAR,acquisition_ready,public,restricted,PanTS,https://github.com/MrGiovanni/PanTS,https://github.com/MrGiovanni/PanTS,0,0,,Do not redistribute converted or staged derivatives
|
| 5 |
+
segmentation,liver,liver-seg-task,Abdomen_Liver,staged_verified,public,unknown,LiTS declared but script uses MSD Task03,https://medicaldecathlon.com/,f2f9890b0576b5dbae03368dff005cc6e93c9512,61,4408461452,0b213dce47051494082ad611d11495dd9551c0d149271ca8d9b1825ff75e836a,Resolve LiTS versus MSD provenance and output directory mismatch
|
| 6 |
+
segmentation,aeropath,aeropath-seg-task,AeroPath,acquisition_ready,public,redistributable,AeroPath,https://zenodo.org/records/10069289,https://zenodo.org/records/10069289,0,0,,Include attribution and license
|
| 7 |
+
segmentation,totalsegmentator,tsg-multiorgan-seg-task,TSG_multi-organ,staged_verified,public,redistributable,TotalSegmentator small v2.0.1,https://zenodo.org/records/10047263,https://zenodo.org/records/10047263,2756,932823155,d6a46067540150dfec635f818076ec808fe2b37e74024127682f2829e683ca33,Freeze source version and include attribution
|
| 8 |
+
segmentation,colon,colon-seg-task,MSD_Colon,staged_verified,public,redistributable,MSD Task10 Colon,https://medicaldecathlon.com/,f2f9890b0576b5dbae03368dff005cc6e93c9512,41,562819052,5a22dc846e27c0e38583ea3cbc6203c2f9e29cf25efb9e2488be0e5173d5f4c4,Include attribution and share-alike license
|
| 9 |
+
segmentation,hepaticvessel,hepaticvessel-seg-task,MSD_HepaticVessel,staged_verified,public,redistributable,MSD Task08 HepaticVessel,https://medicaldecathlon.com/,f2f9890b0576b5dbae03368dff005cc6e93c9512,61,282415129,58beba85c7396bace163a72e43c1ed589126550b1031d7a980056de7fe6b22db,Include attribution and share-alike license
|
| 10 |
+
segmentation,spleen,spleen-seg-task,MSD_Spleen,staged_verified,public,redistributable,MSD Task09 Spleen,https://medicaldecathlon.com/,f2f9890b0576b5dbae03368dff005cc6e93c9512,41,551365228,da42243fa7a339cf05118d2d855dc5704bd128c3db8747ad4b1487d0000f6f50,Include attribution and share-alike license
|
| 11 |
+
segmentation,feta,feta-seg-task,CruzMRI_Feta,externally_blocked,gated,restricted,FeTA,https://zenodo.org/records/4541606,https://zenodo.org/records/4541606,0,0,,Authorized users must acquire data independently
|
| 12 |
+
segmentation,panther_t1,panther-t1-seg-task,PANTHER_Task1,externally_blocked,restricted_access,restricted,PANTHER,https://zenodo.org/records/15192302,609c2a8:eval_seg/stage_panther.py,0,0,,Authorized users must acquire data independently
|
| 13 |
+
segmentation,panther_t2,panther-t2-seg-task,PANTHER_Task2,externally_blocked,restricted_access,restricted,PANTHER,https://zenodo.org/records/15192302,609c2a8:eval_seg/stage_panther.py,0,0,,Authorized users must acquire data independently
|
| 14 |
+
segmentation,heart,heart-seg-task,MSD_Heart,staged_verified,public,redistributable,MSD Task02 Heart,https://medicaldecathlon.com/,f2f9890b0576b5dbae03368dff005cc6e93c9512,41,261610591,1238e5c1618fc5c7539a1d445bc0baec23ff0f3e114edce6c3ac208f39f15d12,Include attribution and share-alike license
|
| 15 |
+
segmentation,prostate,prostate-seg-task,MSD_Prostate,staged_verified,public,redistributable,MSD Task05 Prostate,https://medicaldecathlon.com/,f2f9890b0576b5dbae03368dff005cc6e93c9512,61,105751655,969e79dd9e9c688267c26d9f500a3650fd2aad9e490aa0d8f10c15f04a39a329,Include attribution and share-alike license
|
| 16 |
+
enhancement,ldct-denoising-task,ldct-denoising-task,LDCT_SimNICT,staged_verified,public_library,download_required,AAPM Low Dose CT Grand Challenge,https://www.aapm.org/grandchallenge/lowdosect/,https://www.aapm.org/grandchallenge/lowdosect/,42,41958025,bf70f645d4b5aefe9f8d7db9c060aca709e0d464b8b60dac79dd106dc8aad73e,Download from upstream; do not embed
|
| 17 |
+
enhancement,lidc-idri-denoising-task,lidc-idri-denoising-task,LIDC_IDRI_Denoising,acquisition_ready,public,redistributable,LIDC-IDRI,https://www.cancerimagingarchive.net/collection/lidc-idri/,release_tasks/enhancement/lidc-idri-denoising-task,0,0,,Release-owned harness; freeze selected cases and include attribution
|
| 18 |
+
enhancement,deeplesion-denoising-task,deeplesion-denoising-task,DeepLesion_Denoising,acquisition_ready,public,unknown,NIH DeepLesion,https://nihcc.app.box.com/v/DeepLesion,release_tasks/enhancement/deeplesion-denoising-task,0,0,,Release-owned harness; redistribution grant remains unresolved
|
| 19 |
+
enhancement,mri-sr-task,mri-sr-task,MRI_SR_SRMRI,externally_blocked,application_required,restricted,fastMRI,https://fastmri.med.nyu.edu/,https://fastmri.med.nyu.edu/,0,0,,Authorized users must acquire data independently
|
| 20 |
+
enhancement,brats-t1c-sr-task,brats-t1c-sr-task,BraTS_T1c_SR,externally_blocked,controlled,restricted,BraTS 2023 GLI,https://www.synapse.org/Synapse:syn51156910/wiki/,release_tasks/enhancement/brats-t1c-sr-task,0,0,,Release-owned harness; authorized users must acquire data independently
|
| 21 |
+
enhancement,ixi-t1-sr-task,ixi-t1-sr-task,IXI_T1_SR,acquisition_ready,public,redistributable,IXI T1,https://brain-development.org/ixi-dataset/,release_tasks/enhancement/ixi-t1-sr-task,0,0,,Release-owned harness; include attribution and share-alike license
|
| 22 |
+
enhancement,nih-cxr-sr-task,nih-cxr-sr-task,NIH_CXR_SR,acquisition_ready,public,redistributable,NIH ChestXray14,https://nihcc.app.box.com/v/ChestXray-NIHCC,release_tasks/enhancement/nih-cxr-sr-task,0,0,,Release-owned harness; freeze source provenance
|
| 23 |
+
vqa,vqa-pathvqa-task,pathvqa-task,PathVQA,staged_verified,public,redistributable,PathVQA,https://huggingface.co/datasets/flaviagiammarino/path-vqa,99c166a:eval_vqa/stage_hf_datasets.py,1500,70316761,907890cee4dfc92be1fdc8446cd7e0e563ae7083f6364e0e4d1c6dcf43cc8adf,Include license and source attribution
|
| 24 |
+
vqa,vqa-radvqa-task,vqa-rad-task,VQA_RAD,staged_verified,public,redistributable,VQA-RAD,https://huggingface.co/datasets/flaviagiammarino/vqa-rad,99c166a:eval_vqa/stage_hf_datasets.py,1353,34219470,e841066f8f9800aea57b93bc598ecc6ae7e87a25577f11fc5bd510f9aa9ec1c4,Freeze source revision
|
| 25 |
+
vqa,vqa-medframeqa-task,medframeqa-task,MedFrameQA,staged_verified,public,redistributable,MedFrameQA,https://huggingface.co/datasets/SuhaoYu1020/MedFrameQA,99c166a:eval_vqa/stage_hf_datasets.py,2606,158734712,026bc1509ef0c92b13ffa6becb74b7c667e96feb69f5e655eb99e3f3fe579816,Include attribution
|
| 26 |
+
vqa,vqa-slake-task,slake-task,SLAKE_EN,staged_verified,public,redistributable,SLAKE,https://huggingface.co/datasets/BoKelvin/SLAKE,99c166a:eval_vqa/stage_hf_datasets.py,3183,91232142,8f2d14b3a8a86fc395387d9bc4ed0721b5c8188422737e094b23b7736e41da76,Include attribution
|
| 27 |
+
vqa,vqa-medxpertqa-mm-task,medxpertqa-mm-task,MedXpertQA_MM,staged_verified,public,redistributable,MedXpertQA,https://huggingface.co/datasets/TsinghuaC3I/MedXpertQA,99c166a:eval_vqa/stage_data.py,6872,274860997,43edc7e1f835fb06ed91abce659ed2f9180237a9c834223f7d8ba0aa9bdcc9a0,Include license and source attribution
|
| 28 |
+
vqa,vqa-kvasir-task,vqa-kvasir-task,KvasirVQA,externally_blocked,public_permission_required,restricted,Kvasir-VQA,https://huggingface.co/datasets/SimulaMet-HOST/Kvasir-VQA,release_tasks/vqa/vqa-kvasir-task,0,0,,Release-owned harness; obtain written benchmark permission
|
| 29 |
+
vqa,vqa-omnimedvqa-task,vqa-omnimedvqa-task,OmniMedVQA,externally_blocked,mixed_access,restricted,OmniMedVQA,https://huggingface.co/datasets/foreverbeliever/OmniMedVQA,release_tasks/vqa/vqa-omnimedvqa-task,0,0,,Release-owned harness; independently acquire authorized source subsets
|
| 30 |
+
vqa,vqa-pmc-vqa-task,vqa-pmc-vqa-task,PMC_VQA,staged_verified,public,redistributable,PMC-VQA,https://huggingface.co/datasets/RadGenome/PMC-VQA,b56ae594f794867893143b337b4118a835794647,6001,330226343,ac1ee0a83df8cd56bf0f9856f1f0ae3308c4f822df7d7d3faa5ee3d12cb177c8,Release-owned harness; include attribution and share-alike license
|
| 31 |
+
vqa,vqa-mmmu-medical-task,vqa-mmmu-medical-task,MMMU_Medical,staged_verified,public,redistributable,MMMU medical subsets,https://huggingface.co/datasets/MMMU/MMMU,4619a102cf5ad2da1abf7e220fde1258d2434cb7,444,51307710,b0f8ea48ab60ea35e4fc1ece2a116ff511b5fa070a863fb67d8c861fcfbfec6d,Release-owned harness; freeze five medical validation subsets
|
| 32 |
+
report,mimic-cxr-report-task,mimic-cxr-report-task,MIMIC_CXR_Report,externally_blocked,credentialed_DUA,restricted,MIMIC-CXR,https://physionet.org/content/mimic-cxr/2.1.0/,0fa32bb:eval_report_gen/stage_data.py,0,0,,Authorized users must acquire data independently
|
| 33 |
+
report,iu-xray-report-task,iu-xray-report-task,IU_Xray_Report,acquisition_ready,public_search,unknown,IU Open-i,https://openi.nlm.nih.gov/,release_tasks/report/iu-xray-report-task,0,0,,Release-owned harness; redistribution grant remains unresolved
|
| 34 |
+
report,chexpert-plus-cxr-task,chexpert-plus-cxr-task,CheXpert_Plus_Report,staged_verified,public_mirror,unknown,CheXpert Plus,https://aimi.stanford.edu/datasets/chexpert-plus,0fa32bb:eval_report_gen/stage_hf_datasets.py,501,217459184,ffebd41a80e51358cf1ca1ea630a83f5b9bdabfa193351d2fd59fc6d4f014c10,Hold until exact Stanford terms and source revision are recorded
|
| 35 |
+
report,pathology-caption-100-task,pathology-caption-100-task,Pathology_Caption,staged_verified,auto_gated,restricted,PathCap,https://huggingface.co/datasets/jamessyx/PathCap,17205b19b89ab4ad812a81e9b166d0bcbdaa928e,2503,32300535,c122e73e11cbfdbee02d27b2b61d8cbb6519c378df527aff3489b07c65cf6fe0,local-only staged data; redistribution remains prohibited
|
| 36 |
+
report,pathology-caption-500-task,pathology-caption-500-task,Pathology_Caption,staged_verified,auto_gated,restricted,PathCap,https://huggingface.co/datasets/jamessyx/PathCap,17205b19b89ab4ad812a81e9b166d0bcbdaa928e,2503,32300535,c122e73e11cbfdbee02d27b2b61d8cbb6519c378df527aff3489b07c65cf6fe0,local-only staged data; redistribution remains prohibited
|
| 37 |
+
detection,detection-cxr-abnormality-vindr,vindr-cxr-det-task,VinDrCXR_Detection100,externally_blocked,credentialed_DUA,restricted,VinDr-CXR,https://physionet.org/content/vindr-cxr/1.0.0/,07b8328:eval_det2d/scripts/stage_from_kaggle.sh,0,0,,Authorized users must acquire data independently
|
| 38 |
+
detection,detection-bccd-blood-cell,bccd-det-task,BCCD_Detection100,staged_verified,public,redistributable,BCCD,https://github.com/Shenggan/BCCD_Dataset,07b8328:eval_det2d/scripts/stage_bccd.py,201,15933136,2ac4eb064043f81280982176afff633c42af87df26fff705895ed4598e566175,Include license and source attribution
|
| 39 |
+
detection,detection-dentex-dental-disease,dentex-det-task,DENTEX_Detection100,staged_verified,public,redistributable,DENTEX,https://huggingface.co/datasets/ibrahimhamamci/DENTEX,07b8328:eval_det2d/scripts/stage_dentex.py,201,161673840,dfce6242f6d0e4ef6ade6acb3b3ea2ba4706e7dcddf306518ac6e0cbbce2c314,Include NC-SA terms and attribution
|
| 40 |
+
detection,detection-grazpedwri-wrist-anomaly,grazpedwri-det-task,GRAZPEDWRI_Detection100,staged_verified,public,redistributable,GRAZPEDWRI-DX,https://figshare.com/articles/dataset/GRAZPEDWRI-DX/14825193,07b8328:eval_det2d/scripts/stage_grazpedwri.py,201,24385572,5134ea8eb1a1476b7e8dad2027213da7b843e2334bd3c66596b71b6a72e226fe,Include attribution
|
| 41 |
+
classification,classification-braintumor-mri,braintumor-cls-task,BrainTumorMRI,acquisition_ready,public,redistributable,Brain Tumor MRI,https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset,https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset,0,0,,Include attribution and source provenance
|
| 42 |
+
classification,classification-crc-histology,crc-histology-cls-task,CRC_Histology,acquisition_ready,public,redistributable,NCT-CRC-HE-100K,https://zenodo.org/records/1214456,release_tasks/classification/crc-histology-cls-task,0,0,,Release-owned harness; freeze 100-case split and include attribution
|
| 43 |
+
classification,classification-pcam-metastasis,patchcamelyon-cls-task,PatchCamelyon,acquisition_ready,public,redistributable,PatchCamelyon,https://github.com/basveeling/pcam,release_tasks/classification/patchcamelyon-cls-task,0,0,,Release-owned harness; freeze 100-case split
|
| 44 |
+
classification,classification-chest-pneumonia,chest-xray-pneumonia-cls-task,ChestXrayPneumonia,acquisition_ready,public,redistributable,Kermany chest X-ray pneumonia,https://data.mendeley.com/datasets/rscbjbr9sj/2,release_tasks/classification/chest-xray-pneumonia-cls-task,0,0,,Release-owned harness; freeze 100-case split and include attribution
|
| 45 |
+
classification,classification-isic-skin-lesion,skin-lesion-cls-task,SkinLesionISIC,staged_verified,public,unknown,ISIC Archive,https://www.isic-archive.com/,https://www.isic-archive.com/,203,6261194,0a60dc586144ee544fc5533ec1c6b1313363ac524a060ca9c3768129a90ea05a,Freeze image IDs and their individual licenses before upload
|
| 46 |
+
synthetic,synthetic-synthrad-mrct,synthrad2025-mrct-task,SynthRAD2025_MRCT_HN20,acquisition_ready,public,redistributable,SynthRAD2025,https://zenodo.org/records/15373853,b4fe0cb:eval_synthetic/stage_data.py,0,0,,Include NC terms and attribution
|
| 47 |
+
synthetic,synthetic-ctorg-ctsr,ctorg-ctsr-task,CTORG_CT_SR20,acquisition_ready,public,redistributable,CT-ORG,https://www.cancerimagingarchive.net/collection/ct-org/,b4fe0cb:eval_synthetic/stage_ctsr_data.py,0,0,,Include attribution and freeze source revision
|
| 48 |
+
synthetic,synthetic-msdpancreas-ctsr,msd-pancreas-ctsr-task,MSD_Pancreas_CT_SR20,staged_verified,public,redistributable,MSD Task07 Pancreas,https://medicaldecathlon.com/,b4fe0cb:eval_synthetic/stage_ctsr_data.py,42,1471532418,a575eef6dc619e6073e96c6fef7c1ce14199cc02582e807a2e8e0158ab0aabda,Include attribution and share-alike license
|
| 49 |
+
synthetic,synthetic-totalseg-ctsr,totalsegmentator-ctsr-task,TotalSegmentator_CT_SR20,acquisition_ready,public,redistributable,TotalSegmentator,https://github.com/wasserth/TotalSegmentator,b4fe0cb:eval_synthetic/stage_ctsr_data.py,0,0,,Freeze source version and include attribution
|
manifests/dataset_resolution.json
ADDED
|
@@ -0,0 +1,11 @@
|
|
|
|
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|
|
|
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|
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|
| 1 |
+
{
|
| 2 |
+
"dataset_bytes_uploaded": false,
|
| 3 |
+
"schema_version": 1,
|
| 4 |
+
"staged_local_bytes": 10087648301,
|
| 5 |
+
"statuses": {
|
| 6 |
+
"acquisition_ready": 16,
|
| 7 |
+
"externally_blocked": 9,
|
| 8 |
+
"staged_verified": 23
|
| 9 |
+
},
|
| 10 |
+
"task_count": 48
|
| 11 |
+
}
|
manifests/release_owned_tasks.csv
ADDED
|
@@ -0,0 +1,16 @@
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|
|
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|
|
|
|
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|
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|
|
|
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|
|
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|
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|
| 1 |
+
track,website_task_id,evaluator_task_id,definition_version,authority_ref,canonical_source_status,data_included,readiness
|
| 2 |
+
enhancement,lidc-idri-denoising-task,lidc-idri-denoising-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_metric_assets_and_data
|
| 3 |
+
enhancement,deeplesion-denoising-task,deeplesion-denoising-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_metric_assets_and_data
|
| 4 |
+
enhancement,brats-t1c-sr-task,brats-t1c-sr-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_metric_assets_and_data
|
| 5 |
+
enhancement,ixi-t1-sr-task,ixi-t1-sr-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_metric_assets_and_data
|
| 6 |
+
enhancement,nih-cxr-sr-task,nih-cxr-sr-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_metric_assets_and_data
|
| 7 |
+
vqa,vqa-kvasir-task,vqa-kvasir-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_data_and_permission
|
| 8 |
+
vqa,vqa-omnimedvqa-task,vqa-omnimedvqa-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_authorized_source_selection
|
| 9 |
+
vqa,vqa-pmc-vqa-task,vqa-pmc-vqa-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_frozen_case_manifest
|
| 10 |
+
vqa,vqa-mmmu-medical-task,vqa-mmmu-medical-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_staging
|
| 11 |
+
report,iu-xray-report-task,iu-xray-report-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_metric_assets_and_data
|
| 12 |
+
report,pathology-caption-100-task,pathology-caption-100-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_metric_compatibility_assets_and_data
|
| 13 |
+
report,pathology-caption-500-task,pathology-caption-500-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_metric_compatibility_assets_and_data
|
| 14 |
+
classification,classification-crc-histology,crc-histology-cls-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_frozen_case_manifest
|
| 15 |
+
classification,classification-pcam-metastasis,patchcamelyon-cls-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_frozen_case_manifest
|
| 16 |
+
classification,classification-chest-pneumonia,chest-xray-pneumonia-cls-task,release_owned_v1,1e6471746c94adfd53f552a7bc0b81386f5a5f78,absent_from_locked_and_public_branch,false,blocked_frozen_case_manifest
|
manifests/runtime_archive.json
ADDED
|
@@ -0,0 +1,41 @@
|
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|
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|
|
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|
|
|
| 1 |
+
{
|
| 2 |
+
"schema_version": 1,
|
| 3 |
+
"archive": "automedbench-full-runtime-0.1.0.tar.gz",
|
| 4 |
+
"archive_size": 4297282868,
|
| 5 |
+
"archive_sha256": "b9b7bea8e0e3cb0a03673f00d5b98ba6dfcc3c8329f37f26cf440cec980d38e8",
|
| 6 |
+
"image_count": 8,
|
| 7 |
+
"dataset_content_included": false,
|
| 8 |
+
"credentials_included": false,
|
| 9 |
+
"scan": {
|
| 10 |
+
"outer_members": 97,
|
| 11 |
+
"unique_layers": 44,
|
| 12 |
+
"layer_members": 143878,
|
| 13 |
+
"regular_files": 88216,
|
| 14 |
+
"bytes_scanned": 13749492925,
|
| 15 |
+
"layer_stream_bytes": 9536746496,
|
| 16 |
+
"trusted_base_layers": 9,
|
| 17 |
+
"exact_secret_values_checked": 4
|
| 18 |
+
},
|
| 19 |
+
"base_policy": {
|
| 20 |
+
"base_images": "digest_pinned",
|
| 21 |
+
"base_diff_id_sequences": "locked",
|
| 22 |
+
"exact_secret_scan": "all_layers_and_outer_blobs",
|
| 23 |
+
"heuristic_scan": "all_release_owned_layers"
|
| 24 |
+
},
|
| 25 |
+
"remote": {
|
| 26 |
+
"repo_id": "MitakaKuma/AutoMedBench-Full-release",
|
| 27 |
+
"path": "runtime/automedbench-full-runtime-0.1.0.tar.gz",
|
| 28 |
+
"verified_revision": "cbeb96a85325da6dbe039a5a0cf6053293aa7ba6",
|
| 29 |
+
"verified_size": 4297282868,
|
| 30 |
+
"verified_lfs_sha256": "b9b7bea8e0e3cb0a03673f00d5b98ba6dfcc3c8329f37f26cf440cec980d38e8",
|
| 31 |
+
"repository_private": true,
|
| 32 |
+
"anonymous_access_denied": true
|
| 33 |
+
},
|
| 34 |
+
"local_cleanup": {
|
| 35 |
+
"archive_removed_after_remote_verification": true,
|
| 36 |
+
"checksum_sidecar_removed_after_remote_verification": true,
|
| 37 |
+
"namespaced_image_tags_removed": 8,
|
| 38 |
+
"global_docker_prune_performed": false
|
| 39 |
+
},
|
| 40 |
+
"status": "private_upload_verified"
|
| 41 |
+
}
|
manifests/runtime_images.csv
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
image_index,logical_image_id,role,track,task_count,combination_count,tier_coverage,dataset_bytes,release_version,image_digest,status
|
| 2 |
+
1,shared-agent-runtime,agent,all,48,96,lite+standard,excluded,0.1.0,sha256:c442c21239b697ce5aa46288b4c019b95a7787644b828ac652dbc8939e45b8e3,uploaded_verified
|
| 3 |
+
2,evaluator-segmentation,evaluator,segmentation,14,28,lite+standard,excluded,0.1.0,sha256:514b97a2b36731d6934624b3324dbf7910c73a6252e2ab288d029ff4dde90f36,uploaded_verified
|
| 4 |
+
3,evaluator-enhancement,evaluator,enhancement,7,14,lite+standard,excluded,0.1.0,sha256:466e3c93f4578521dc98a03c7a6cb734b68fbdfd3a5238739ea70b318b9eab2a,uploaded_verified
|
| 5 |
+
4,evaluator-vqa,evaluator,vqa,9,18,lite+standard,excluded,0.1.0,sha256:7ebd2db03afd3230f081e4500d90c0ac983ef91e97c19f075766534c2c8537f5,uploaded_verified
|
| 6 |
+
5,evaluator-report,evaluator,report,5,10,lite+standard,excluded,0.1.0,sha256:5ff34671b22dbbb6f154b11d8c022c6c96df12a91d3902c9bd9e0b258e93f852,uploaded_verified
|
| 7 |
+
6,evaluator-detection,evaluator,detection,4,8,lite+standard,excluded,0.1.0,sha256:9354fe8ac332dab7848aa87445be62b9e3182af4ebabf678ca54fa1a15881496,uploaded_verified
|
| 8 |
+
7,evaluator-classification,evaluator,classification,5,10,lite+standard,excluded,0.1.0,sha256:18d582f6d9304c234258523f9b6b44a99a42dfbea64daffc86bebf15e7afa704,uploaded_verified
|
| 9 |
+
8,evaluator-synthetic,evaluator,synthetic,4,8,lite+standard,excluded,0.1.0,sha256:14a8cdf9490976bd9f940320ebdd2fdcaec1a698f9b289a0c7183efe29744309,uploaded_verified
|
manifests/source_lock.json
ADDED
|
@@ -0,0 +1,44 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"matrix_authority": {
|
| 3 |
+
"repository": "AutoMedBench/AutoMedBench.github.io",
|
| 4 |
+
"ref": "1e6471746c94adfd53f552a7bc0b81386f5a5f78",
|
| 5 |
+
"url": "https://automedbench.github.io/"
|
| 6 |
+
},
|
| 7 |
+
"tracks": {
|
| 8 |
+
"segmentation": {
|
| 9 |
+
"repository": "KumaKuma2002/MedAgentsBench",
|
| 10 |
+
"branch": "main",
|
| 11 |
+
"ref": "609c2a8df21addfff5dbfb680a7263fb8cf91d99"
|
| 12 |
+
},
|
| 13 |
+
"enhancement": {
|
| 14 |
+
"repository": "KumaKuma2002/MedAgentsBench",
|
| 15 |
+
"branch": "image-enhancement",
|
| 16 |
+
"ref": "c777f3371f4a772ddbfb131ad4ec9e1963be0cc9"
|
| 17 |
+
},
|
| 18 |
+
"vqa": {
|
| 19 |
+
"repository": "KumaKuma2002/MedAgentsBench",
|
| 20 |
+
"branch": "vqa",
|
| 21 |
+
"ref": "99c166a3546bba348dd618fd310f5d4b8821e77f"
|
| 22 |
+
},
|
| 23 |
+
"report": {
|
| 24 |
+
"repository": "KumaKuma2002/MedAgentsBench",
|
| 25 |
+
"branch": "report-gen",
|
| 26 |
+
"ref": "0fa32bb2a194c3ffb3cfb67e5e49a7c215dc7072"
|
| 27 |
+
},
|
| 28 |
+
"detection": {
|
| 29 |
+
"repository": "KumaKuma2002/MedAgentsBench",
|
| 30 |
+
"branch": "det2d",
|
| 31 |
+
"ref": "07b8328a87f9c434dc67f1f8a5753939a30ba24e"
|
| 32 |
+
},
|
| 33 |
+
"classification": {
|
| 34 |
+
"repository": "KumaKuma2002/MedAgentsBench",
|
| 35 |
+
"branch": "classification",
|
| 36 |
+
"ref": "0e12fb300b3371343cbfb7c9c234c74d551fb1c1"
|
| 37 |
+
},
|
| 38 |
+
"synthetic": {
|
| 39 |
+
"repository": "KumaKuma2002/MedAgentsBench",
|
| 40 |
+
"branch": "synthetic",
|
| 41 |
+
"ref": "b4fe0cb69257c4111408c0327c9353cd85b34ba3"
|
| 42 |
+
}
|
| 43 |
+
}
|
| 44 |
+
}
|
manifests/task_matrix.csv
ADDED
|
@@ -0,0 +1,97 @@
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| 1 |
+
combination_index,track,task_index,website_task_id,evaluator_task_id,tier,source_ref,harness_status,local_data_status
|
| 2 |
+
1,segmentation,1,kidney,kidney-seg-task,lite,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,acquisition_ready
|
| 3 |
+
2,segmentation,1,kidney,kidney-seg-task,standard,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,acquisition_ready
|
| 4 |
+
3,segmentation,2,pancreas,pancreas-seg-task,lite,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,acquisition_ready
|
| 5 |
+
4,segmentation,2,pancreas,pancreas-seg-task,standard,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,acquisition_ready
|
| 6 |
+
5,segmentation,3,pancreas_oar,pancreas-oar-seg-task,lite,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,acquisition_ready
|
| 7 |
+
6,segmentation,3,pancreas_oar,pancreas-oar-seg-task,standard,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,acquisition_ready
|
| 8 |
+
7,segmentation,4,liver,liver-seg-task,lite,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,staged_verified
|
| 9 |
+
8,segmentation,4,liver,liver-seg-task,standard,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,staged_verified
|
| 10 |
+
9,segmentation,5,aeropath,aeropath-seg-task,lite,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,acquisition_ready
|
| 11 |
+
10,segmentation,5,aeropath,aeropath-seg-task,standard,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,acquisition_ready
|
| 12 |
+
11,segmentation,6,totalsegmentator,tsg-multiorgan-seg-task,lite,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,staged_verified
|
| 13 |
+
12,segmentation,6,totalsegmentator,tsg-multiorgan-seg-task,standard,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,staged_verified
|
| 14 |
+
13,segmentation,7,colon,colon-seg-task,lite,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,staged_verified
|
| 15 |
+
14,segmentation,7,colon,colon-seg-task,standard,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,staged_verified
|
| 16 |
+
15,segmentation,8,hepaticvessel,hepaticvessel-seg-task,lite,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,staged_verified
|
| 17 |
+
16,segmentation,8,hepaticvessel,hepaticvessel-seg-task,standard,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,staged_verified
|
| 18 |
+
17,segmentation,9,spleen,spleen-seg-task,lite,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,staged_verified
|
| 19 |
+
18,segmentation,9,spleen,spleen-seg-task,standard,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,staged_verified
|
| 20 |
+
19,segmentation,10,feta,feta-seg-task,lite,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,externally_blocked
|
| 21 |
+
20,segmentation,10,feta,feta-seg-task,standard,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,externally_blocked
|
| 22 |
+
21,segmentation,11,panther_t1,panther-t1-seg-task,lite,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,externally_blocked
|
| 23 |
+
22,segmentation,11,panther_t1,panther-t1-seg-task,standard,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,externally_blocked
|
| 24 |
+
23,segmentation,12,panther_t2,panther-t2-seg-task,lite,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,externally_blocked
|
| 25 |
+
24,segmentation,12,panther_t2,panther-t2-seg-task,standard,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,externally_blocked
|
| 26 |
+
25,segmentation,13,heart,heart-seg-task,lite,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,staged_verified
|
| 27 |
+
26,segmentation,13,heart,heart-seg-task,standard,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,staged_verified
|
| 28 |
+
27,segmentation,14,prostate,prostate-seg-task,lite,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,staged_verified
|
| 29 |
+
28,segmentation,14,prostate,prostate-seg-task,standard,609c2a8df21addfff5dbfb680a7263fb8cf91d99,committed,staged_verified
|
| 30 |
+
29,enhancement,1,ldct-denoising-task,ldct-denoising-task,lite,c777f3371f4a772ddbfb131ad4ec9e1963be0cc9,committed,staged_verified
|
| 31 |
+
30,enhancement,1,ldct-denoising-task,ldct-denoising-task,standard,c777f3371f4a772ddbfb131ad4ec9e1963be0cc9,committed,staged_verified
|
| 32 |
+
31,enhancement,2,lidc-idri-denoising-task,lidc-idri-denoising-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 33 |
+
32,enhancement,2,lidc-idri-denoising-task,lidc-idri-denoising-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 34 |
+
33,enhancement,3,deeplesion-denoising-task,deeplesion-denoising-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 35 |
+
34,enhancement,3,deeplesion-denoising-task,deeplesion-denoising-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 36 |
+
35,enhancement,4,mri-sr-task,mri-sr-task,lite,c777f3371f4a772ddbfb131ad4ec9e1963be0cc9,committed,externally_blocked
|
| 37 |
+
36,enhancement,4,mri-sr-task,mri-sr-task,standard,c777f3371f4a772ddbfb131ad4ec9e1963be0cc9,committed,externally_blocked
|
| 38 |
+
37,enhancement,5,brats-t1c-sr-task,brats-t1c-sr-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,externally_blocked
|
| 39 |
+
38,enhancement,5,brats-t1c-sr-task,brats-t1c-sr-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,externally_blocked
|
| 40 |
+
39,enhancement,6,ixi-t1-sr-task,ixi-t1-sr-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 41 |
+
40,enhancement,6,ixi-t1-sr-task,ixi-t1-sr-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 42 |
+
41,enhancement,7,nih-cxr-sr-task,nih-cxr-sr-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 43 |
+
42,enhancement,7,nih-cxr-sr-task,nih-cxr-sr-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 44 |
+
43,vqa,1,vqa-pathvqa-task,pathvqa-task,lite,99c166a3546bba348dd618fd310f5d4b8821e77f,committed,staged_verified
|
| 45 |
+
44,vqa,1,vqa-pathvqa-task,pathvqa-task,standard,99c166a3546bba348dd618fd310f5d4b8821e77f,committed,staged_verified
|
| 46 |
+
45,vqa,2,vqa-radvqa-task,vqa-rad-task,lite,99c166a3546bba348dd618fd310f5d4b8821e77f,committed,staged_verified
|
| 47 |
+
46,vqa,2,vqa-radvqa-task,vqa-rad-task,standard,99c166a3546bba348dd618fd310f5d4b8821e77f,committed,staged_verified
|
| 48 |
+
47,vqa,3,vqa-medframeqa-task,medframeqa-task,lite,99c166a3546bba348dd618fd310f5d4b8821e77f,committed,staged_verified
|
| 49 |
+
48,vqa,3,vqa-medframeqa-task,medframeqa-task,standard,99c166a3546bba348dd618fd310f5d4b8821e77f,committed,staged_verified
|
| 50 |
+
49,vqa,4,vqa-slake-task,slake-task,lite,99c166a3546bba348dd618fd310f5d4b8821e77f,committed,staged_verified
|
| 51 |
+
50,vqa,4,vqa-slake-task,slake-task,standard,99c166a3546bba348dd618fd310f5d4b8821e77f,committed,staged_verified
|
| 52 |
+
51,vqa,5,vqa-medxpertqa-mm-task,medxpertqa-mm-task,lite,99c166a3546bba348dd618fd310f5d4b8821e77f,committed,staged_verified
|
| 53 |
+
52,vqa,5,vqa-medxpertqa-mm-task,medxpertqa-mm-task,standard,99c166a3546bba348dd618fd310f5d4b8821e77f,committed,staged_verified
|
| 54 |
+
53,vqa,6,vqa-kvasir-task,vqa-kvasir-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,externally_blocked
|
| 55 |
+
54,vqa,6,vqa-kvasir-task,vqa-kvasir-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,externally_blocked
|
| 56 |
+
55,vqa,7,vqa-omnimedvqa-task,vqa-omnimedvqa-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,externally_blocked
|
| 57 |
+
56,vqa,7,vqa-omnimedvqa-task,vqa-omnimedvqa-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,externally_blocked
|
| 58 |
+
57,vqa,8,vqa-pmc-vqa-task,vqa-pmc-vqa-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,staged_verified
|
| 59 |
+
58,vqa,8,vqa-pmc-vqa-task,vqa-pmc-vqa-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,staged_verified
|
| 60 |
+
59,vqa,9,vqa-mmmu-medical-task,vqa-mmmu-medical-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,staged_verified
|
| 61 |
+
60,vqa,9,vqa-mmmu-medical-task,vqa-mmmu-medical-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,staged_verified
|
| 62 |
+
61,report,1,mimic-cxr-report-task,mimic-cxr-report-task,lite,0fa32bb2a194c3ffb3cfb67e5e49a7c215dc7072,committed,externally_blocked
|
| 63 |
+
62,report,1,mimic-cxr-report-task,mimic-cxr-report-task,standard,0fa32bb2a194c3ffb3cfb67e5e49a7c215dc7072,committed,externally_blocked
|
| 64 |
+
63,report,2,iu-xray-report-task,iu-xray-report-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 65 |
+
64,report,2,iu-xray-report-task,iu-xray-report-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 66 |
+
65,report,3,chexpert-plus-cxr-task,chexpert-plus-cxr-task,lite,0fa32bb2a194c3ffb3cfb67e5e49a7c215dc7072,committed,staged_verified
|
| 67 |
+
66,report,3,chexpert-plus-cxr-task,chexpert-plus-cxr-task,standard,0fa32bb2a194c3ffb3cfb67e5e49a7c215dc7072,committed,staged_verified
|
| 68 |
+
67,report,4,pathology-caption-100-task,pathology-caption-100-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,staged_verified
|
| 69 |
+
68,report,4,pathology-caption-100-task,pathology-caption-100-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,staged_verified
|
| 70 |
+
69,report,5,pathology-caption-500-task,pathology-caption-500-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,staged_verified
|
| 71 |
+
70,report,5,pathology-caption-500-task,pathology-caption-500-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,staged_verified
|
| 72 |
+
71,detection,1,detection-cxr-abnormality-vindr,vindr-cxr-det-task,lite,07b8328a87f9c434dc67f1f8a5753939a30ba24e,committed,externally_blocked
|
| 73 |
+
72,detection,1,detection-cxr-abnormality-vindr,vindr-cxr-det-task,standard,07b8328a87f9c434dc67f1f8a5753939a30ba24e,committed,externally_blocked
|
| 74 |
+
73,detection,2,detection-bccd-blood-cell,bccd-det-task,lite,07b8328a87f9c434dc67f1f8a5753939a30ba24e,committed,staged_verified
|
| 75 |
+
74,detection,2,detection-bccd-blood-cell,bccd-det-task,standard,07b8328a87f9c434dc67f1f8a5753939a30ba24e,committed,staged_verified
|
| 76 |
+
75,detection,3,detection-dentex-dental-disease,dentex-det-task,lite,07b8328a87f9c434dc67f1f8a5753939a30ba24e,committed,staged_verified
|
| 77 |
+
76,detection,3,detection-dentex-dental-disease,dentex-det-task,standard,07b8328a87f9c434dc67f1f8a5753939a30ba24e,committed,staged_verified
|
| 78 |
+
77,detection,4,detection-grazpedwri-wrist-anomaly,grazpedwri-det-task,lite,07b8328a87f9c434dc67f1f8a5753939a30ba24e,committed,staged_verified
|
| 79 |
+
78,detection,4,detection-grazpedwri-wrist-anomaly,grazpedwri-det-task,standard,07b8328a87f9c434dc67f1f8a5753939a30ba24e,committed,staged_verified
|
| 80 |
+
79,classification,1,classification-braintumor-mri,braintumor-cls-task,lite,0e12fb300b3371343cbfb7c9c234c74d551fb1c1,committed,acquisition_ready
|
| 81 |
+
80,classification,1,classification-braintumor-mri,braintumor-cls-task,standard,0e12fb300b3371343cbfb7c9c234c74d551fb1c1,committed,acquisition_ready
|
| 82 |
+
81,classification,2,classification-crc-histology,crc-histology-cls-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 83 |
+
82,classification,2,classification-crc-histology,crc-histology-cls-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 84 |
+
83,classification,3,classification-pcam-metastasis,patchcamelyon-cls-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 85 |
+
84,classification,3,classification-pcam-metastasis,patchcamelyon-cls-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 86 |
+
85,classification,4,classification-chest-pneumonia,chest-xray-pneumonia-cls-task,lite,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 87 |
+
86,classification,4,classification-chest-pneumonia,chest-xray-pneumonia-cls-task,standard,release-owned-v1@1e6471746c94adfd53f552a7bc0b81386f5a5f78,release_owned,acquisition_ready
|
| 88 |
+
87,classification,5,classification-isic-skin-lesion,skin-lesion-cls-task,lite,0e12fb300b3371343cbfb7c9c234c74d551fb1c1,committed,staged_verified
|
| 89 |
+
88,classification,5,classification-isic-skin-lesion,skin-lesion-cls-task,standard,0e12fb300b3371343cbfb7c9c234c74d551fb1c1,committed,staged_verified
|
| 90 |
+
89,synthetic,1,synthetic-synthrad-mrct,synthrad2025-mrct-task,lite,b4fe0cb69257c4111408c0327c9353cd85b34ba3,committed,acquisition_ready
|
| 91 |
+
90,synthetic,1,synthetic-synthrad-mrct,synthrad2025-mrct-task,standard,b4fe0cb69257c4111408c0327c9353cd85b34ba3,committed,acquisition_ready
|
| 92 |
+
91,synthetic,2,synthetic-ctorg-ctsr,ctorg-ctsr-task,lite,b4fe0cb69257c4111408c0327c9353cd85b34ba3,committed,acquisition_ready
|
| 93 |
+
92,synthetic,2,synthetic-ctorg-ctsr,ctorg-ctsr-task,standard,b4fe0cb69257c4111408c0327c9353cd85b34ba3,committed,acquisition_ready
|
| 94 |
+
93,synthetic,3,synthetic-msdpancreas-ctsr,msd-pancreas-ctsr-task,lite,b4fe0cb69257c4111408c0327c9353cd85b34ba3,committed,staged_verified
|
| 95 |
+
94,synthetic,3,synthetic-msdpancreas-ctsr,msd-pancreas-ctsr-task,standard,b4fe0cb69257c4111408c0327c9353cd85b34ba3,committed,staged_verified
|
| 96 |
+
95,synthetic,4,synthetic-totalseg-ctsr,totalsegmentator-ctsr-task,lite,b4fe0cb69257c4111408c0327c9353cd85b34ba3,committed,acquisition_ready
|
| 97 |
+
96,synthetic,4,synthetic-totalseg-ctsr,totalsegmentator-ctsr-task,standard,b4fe0cb69257c4111408c0327c9353cd85b34ba3,committed,acquisition_ready
|
runtime/automedbench-full-runtime-0.1.0.tar.gz
ADDED
|
@@ -0,0 +1,3 @@
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|
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
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runtime/automedbench-full-runtime-0.1.0.tar.gz.sha256
ADDED
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version https://git-lfs.github.com/spec/v1
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size 105
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runtime/images.lock.json
ADDED
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@@ -0,0 +1,89 @@
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|
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|
|
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|
|
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{
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{
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{
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| 35 |
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|
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|
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{
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| 50 |
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|
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|
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|
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|
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|
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|
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|
| 65 |
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| 66 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
schemas/task.schema.json
ADDED
|
@@ -0,0 +1,137 @@
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|
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|
| 1 |
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{
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| 2 |
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|
| 3 |
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"$id": "https://automedbench.github.io/schemas/full-release-task-v2.json",
|
| 4 |
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"title": "AutoMedBench Full data-free task package",
|
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|
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|
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|
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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"evaluator_task_id",
|
| 13 |
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"tiers",
|
| 14 |
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"source",
|
| 15 |
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"evaluator",
|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
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],
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"properties": {
|
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| 23 |
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|
| 24 |
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"track": {
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| 25 |
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"enum": [
|
| 26 |
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|
| 27 |
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"enhancement",
|
| 28 |
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"vqa",
|
| 29 |
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"report",
|
| 30 |
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"detection",
|
| 31 |
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"classification",
|
| 32 |
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"synthetic"
|
| 33 |
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]
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| 34 |
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},
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"website_task_id": {"type": "string", "pattern": "^[a-z0-9][a-z0-9._-]*$"},
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|
| 38 |
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"type": "array",
|
| 39 |
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"prefixItems": [{"const": "lite"}, {"const": "standard"}],
|
| 40 |
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|
| 41 |
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|
| 42 |
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"required": ["ref", "config_path", "config_sha256", "staging_manifest_sha256"],
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| 48 |
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"ref": {"type": "string", "minLength": 1},
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| 50 |
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| 51 |
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"type": "string",
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"pattern": "^source/(?!/)(?!.*(?:^|/)\\.\\.(?:/|$)).+$"
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| 53 |
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"evaluator": {
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|
| 60 |
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|
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"required": ["adapter", "entrypoint", "network_required"],
|
| 62 |
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| 63 |
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"adapter": {"type": "string", "minLength": 1},
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| 64 |
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"entrypoint": {"type": "string", "pattern": "^source/"},
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| 65 |
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"network_required": {"const": false}
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}
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},
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"dataset": {
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"type": "object",
|
| 70 |
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|
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"required": [
|
| 72 |
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"included",
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| 73 |
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|
| 74 |
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|
| 75 |
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"access",
|
| 76 |
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"license",
|
| 77 |
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"upstream",
|
| 78 |
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"upstream_url",
|
| 79 |
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"release_gate",
|
| 80 |
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"public_mount",
|
| 81 |
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"private_mount"
|
| 82 |
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],
|
| 83 |
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"properties": {
|
| 84 |
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"included": {"const": false},
|
| 85 |
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"data_dir_name": {"type": "string"},
|
| 86 |
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"policy": {
|
| 87 |
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"enum": ["redistributable", "download_required", "restricted", "unknown"]
|
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},
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"access": {"type": "string"},
|
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"license": {"type": "string"},
|
| 91 |
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"upstream": {"type": "string", "minLength": 1},
|
| 92 |
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"upstream_url": {"type": "string", "pattern": "^https://"},
|
| 93 |
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"release_gate": {"type": "string"},
|
| 94 |
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"public_mount": {"const": "/data/public"},
|
| 95 |
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"private_mount": {"const": "/data/private"}
|
| 96 |
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}
|
| 97 |
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},
|
| 98 |
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"input_contract": {
|
| 99 |
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| 100 |
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|
| 101 |
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"required": ["unit", "filename"],
|
| 102 |
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"properties": {
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| 103 |
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"unit": {"enum": ["case", "question"]},
|
| 104 |
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"filename": {"type": ["string", "null"]}
|
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}
|
| 106 |
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},
|
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"output_contract": {"type": "object", "minProperties": 2},
|
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|
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|
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|
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|
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"required": [
|
| 114 |
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"name",
|
| 115 |
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"destination",
|
| 116 |
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"required_for_tiers",
|
| 117 |
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"provisioning",
|
| 118 |
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"integrity",
|
| 119 |
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"included"
|
| 120 |
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],
|
| 121 |
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"properties": {
|
| 122 |
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"name": {"type": "string", "minLength": 1},
|
| 123 |
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"destination": {"type": "string", "pattern": "^/models/"},
|
| 124 |
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"required_for_tiers": {
|
| 125 |
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"type": "array",
|
| 126 |
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"items": {"enum": ["lite", "standard"]},
|
| 127 |
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"minItems": 1,
|
| 128 |
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"uniqueItems": true
|
| 129 |
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},
|
| 130 |
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"provisioning": {"const": "user_supplied_read_only_mount"},
|
| 131 |
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"integrity": {"const": "sha256_must_be_verified_before_use"},
|
| 132 |
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"included": {"const": false}
|
| 133 |
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}
|
| 134 |
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}
|
| 135 |
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}
|
| 136 |
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}
|
| 137 |
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}
|
tasks/_package_manifest.json
ADDED
|
@@ -0,0 +1,682 @@
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| 1 |
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| 78 |
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| 84 |
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| 88 |
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| 89 |
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| 103 |
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| 105 |
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| 111 |
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| 112 |
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| 113 |
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| 114 |
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| 115 |
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| 116 |
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| 117 |
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