| --- |
| license: cc-by-4.0 |
| language: [en] |
| pretty_name: DrugDiscoveryBench |
| tags: [drug-discovery, biology, chemistry, benchmark, agent] |
| extra_gated_prompt: | |
| This dataset contains evaluation-only ground truth and rubrics. Do not redistribute them or use them to train or fine-tune models to game the benchmark. By requesting access you agree to use the protected fields only for evaluation. |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: train.parquet |
| --- |
| |
| # DrugDiscoveryBench |
|
|
| Authorized Edison packaging of [ScaleAI/DrugDiscoveryBench](https://huggingface.co/datasets/ScaleAI/DrugDiscoveryBench) for agent evaluation. It contains the benchmark's 82 tasks in one `train` split and preserves the source's evaluation-only access conditions. |
|
|
| Source revision: `10cbbbb5da6f0fa46a6567c7cae0cbb3baa6c7cc`. |
|
|
| ## Capability counts |
| | capability | tasks | |
| | --- | ---: | |
| | `cheminformatics` | 10 | |
| | `database_screening` | 14 | |
| | `molecular_biology` | 7 | |
| | `patent_mining` | 13 | |
| | `sar_affinity` | 7 | |
| | `structural_reasoning` | 19 | |
| | `target_id_genetics` | 12 | |
|
|
| ## Schema |
| Each row contains a stable `uuid`, source `question_id` and `source_category`, the agent-visible `question`, `grader_type`, protected `ground_truth` and source metadata in `params`, and the normalized `rubric`. `input_files` is a compact JSON list of task-local filenames. `data_storage_uris` is a list of matching DEV DSS `data_entry:` URIs in the same order. The rubric's criteria have stable IDs, `correctness` or `methodology` category, and signed numeric point weights. |
|
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| Outcome criteria use IDs `outcome_NNN_positive` or `outcome_NNN_negative`; process criteria use the equivalent `process_NNN_*` IDs. The suffix is the criterion's signed-point polarity: positive weights award points when met, while negative weights deduct points when the detrimental condition is met. |
|
|
| ## Load |
| ```python |
| from datasets import load_dataset |
| |
| tasks = load_dataset("EdisonScientific/DrugDiscoveryBench", split="train") |
| ``` |
|
|
