---
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