---
license: mit
language:
- en
task_categories:
- text-classification
tags:
- clarus
- clinical
- quad-coupling
- protocol-deviation
- staffing
- adjudication
- missingness
pretty_name: Clinical Quad Protocol Deviation Staffing Drift Adjudication Variance Missingness Bias v0.2
---

Clinical Quad Protocol Deviation Staffing Drift Adjudication Variance Missingness Bias v0.2

What this dataset does

It tests whether a model can detect operational collapse risk in trial conduct.

The quad nodes

- protocol_deviation  
- staffing_drift  
- adjudication_variance  
- missingness_bias  

Labels

coherent  
- stable staffing  
- low drift and low bias  
- operations remain controlled  

tradeoff  
- mixed strain  
- issues exist but do not meet collapse pattern  

collapse_risk  
- all level nodes high and staffing drift present  
- process control fails across the trial pipeline  

What changed in v0.2

- Fixed repo name typo from linical to clinical  
- Version bumped so scorer updates are visible  
- New scorer with validation, confusion, and error sampling  
- Added risk_score and rule_pred diagnostics  

Files

data/train.csv  
data/test.csv  
scorer.py  

Run scoring

python scorer.py --preds_csv predictions.csv --gold_csv data/test.csv