ClarusC64/clinical-quad-signal-detection-drift-ae-coding-variance-unblinding-risk-dsmb-decision-delay-v0.1
Clinical Quad: Signal Detection Drift × AE Coding Variance × Unblinding Risk × DSMB Decision Delay This dataset targets safety governance collapse. Signals weaken or shift.AE coding diverges across sites.Unblinding pressure rises.The DSMB response slows. The quad can turn a manageable safety issue into a governance failure. Variables signal_detection_drift (low | medium | high) ae_coding_variance (low | medium | high) unblinding_risk (low | medium | high)… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-signal-detection-drift-ae-coding-variance-unblinding-risk-dsmb-decision-delay-v0.1.
Clinical Quad: Signal Detection Drift × AE Coding Variance × Unblinding Risk × DSMB Decision Delay
This dataset targets safety governance collapse.
Signals weaken or shift. AE coding diverges across sites. Unblinding pressure rises. The DSMB response slows.
The quad can turn a manageable safety issue into a governance failure.
Variables
- signaldetectiondrift (low | medium | high)
- aecodingvariance (low | medium | high)
- unblinding_risk (low | medium | high)
- dsmbdecisiondelay (low | medium | high)
Labels
- coherent
- tradeoff
- collapse_risk
Collapse rule
All four dimensions high.
Why it matters
You want models to spot when “we are monitoring safety” is no longer true in practice.