Datasets:
id int64 1 10 | recruitment stringclasses 3
values | site_mix stringclasses 2
values | endpoint stringclasses 3
values | protocol_change stringclasses 3
values | signal stringclasses 10
values | label int64 0 2 |
|---|---|---|---|---|---|---|
1 | on_target | balanced | primary_met | none | all nodes aligned | 0 |
2 | slipping | balanced | primary_met | minor | early strain but recoverable | 1 |
3 | slipping | skewed | primary_missed | minor | site mix drift undermines endpoint | 1 |
4 | off_target | skewed | primary_missed | major | protocol shifts chase recruitment failure | 2 |
5 | on_target | skewed | secondary_only | minor | endpoint tension from site bias | 1 |
6 | off_target | balanced | secondary_only | major | endpoint rewrite to mask enrollment collapse | 2 |
7 | slipping | skewed | secondary_only | major | quad misalignment locks in collapse | 2 |
8 | on_target | balanced | primary_met | minor | small change with intact coherence | 0 |
9 | on_target | skewed | primary_met | none | site skew but endpoint still robust | 1 |
10 | off_target | skewed | primary_missed | major | recruitment failure drives unstable decisions | 2 |
Clinical Quad Recruitment Endpoint Coherence Collapse v0.2
What this dataset does
It tests whether a model can detect when recruitment pressure drives endpoint instability.
The quad nodes
- recruitment
- site_mix
- endpoint
- protocol_change
Labels
0 coherent
- recruitment on target
- sites balanced
- primary endpoint met
- no major protocol change
1 tradeoff
- some drift or tension
- endpoint credibility pressured but not fully broken
2 collapse
- recruitment failure drives major protocol changes
- endpoint integrity collapses under site drift and missed primary outcomes
What changed in v0.2
- Version bumped so scorer updates are visible
- New scorer with validation, confusion, and error sampling
- Added rule_pred and risk_score diagnostics
- Predictions can be label, prediction, or output text
Files
data/train.csv
data/test.csv
scorer.py
Run scoring
python scorer.py --preds_csv predictions.csv --gold_csv data/test.csv
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