ClarusC64/clinical-quad-adjudication-drift-endpoint-reclassification-timing-pressure-v0.1
Clarus Clinical Quad Coupling Adjudication Drift Endpoint Reclassification Timing Pressure v0.1 What this dataset isThis dataset tests whether a model can detect endpoint adjudication drift driven by four interacting nodes. Quad coupling nodes Clustered endpoint reclassification Source data delay or missing uploads Exposure or dose documentation gaps Governance or interim analysis pressure Input One vignette OutputReturn strict JSON only. Required output JSON keys… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-adjudication-drift-endpoint-reclassification-timing-pressure-v0.1.
Clarus Clinical Quad Coupling Adjudication Drift Endpoint Reclassification Timing Pressure v0.1
What this dataset is This dataset tests whether a model can detect endpoint adjudication drift driven by four interacting nodes.
Quad coupling nodes
- Clustered endpoint reclassification
- Source data delay or missing uploads
- Exposure or dose documentation gaps
- Governance or interim analysis pressure
Input
- One vignette
Output Return strict JSON only.
Required output JSON keys
- adjudicationdriftrisk
- risk_type
- driver_nodes
- recommended_action
- action_detail
- rationale
- confidence
Files
- data/train.csv
- data/test.csv
- scorer.py
Scoring
- Required key presence
- Risk classification
- Risk type match
- Driver node overlap
- Recommended action match
- Action detail completeness
- Rationale length
- Confidence within 0 to 1
Run scoring Create JSONL {"id":"ADJ-T01","output":"{...your json...}"}
Run python scorer.py --goldcsv data/test.csv --predsjsonl your_outputs.jsonl
