| --- |
| license: mit |
| language: |
| - en |
| task_categories: |
| - text-generation |
| tags: |
| - clarus |
| - clinical |
| - epro |
| - patient-reported-outcomes |
| - quad-coupling |
| pretty_name: Clinical Quad Coupling ePRO Compliance Device Update Notification Bias Site Coaching Governance Interim v0.1 |
| --- |
| |
| Clarus Clinical Quad Coupling ePRO Integrity v0.1 |
|
|
| What this dataset is |
| This dataset tests whether a model can detect ePRO integrity risk driven by four interacting nodes. |
|
|
| Quad coupling nodes |
| - Compliance drop or patterned missingness |
| - Device or app update and reminder configuration |
| - Site influence or coaching and backfill behavior |
| - Governance pressure from interim reads or submission reliance |
|
|
| Input |
| - One vignette |
|
|
| Output |
| Return strict JSON only. |
|
|
| Required output JSON keys |
| - epro_integrity_risk |
| - risk_type |
| - driver_nodes |
| - recommended_action |
| - action_detail |
| - rationale |
| - confidence |
|
|
| Files |
| - data/train.csv |
| - data/test.csv |
| - scorer.py |
|
|
| Run scoring |
| Create JSONL predictions |
| {"id":"EPRO-T01","output":"{...your json...}"} |
|
|
| Run |
| python scorer.py --gold_csv data/test.csv --preds_jsonl preds.jsonl |
