ClarusC64/clinical-quad-baseline-risk-adherence-pk-variance-genetic-factor-response-loss-v0.1

What this repo does

This dataset models efficacy response divergence as a basin exit event in patient response space. It predicts when the interaction between baseline risk, adherence, pharmacokinetic variance, and genetic response factor increases the probability of response loss under treatment.

Core quad

baselineriskscore adherenceindex pkvarianceindex geneticresponse_factor

Prediction target

labelresponseloss

Row structure

Each row represents a patient response state snapshot during treatment. The model predicts whether coupled risk and exposure dynamics cause the patient to exit the response regime within the next assessment window.

Files

data/train.csv data/tester.csv scorer.py

Evaluation

Run predictions on tester.csv Add column prediction Score with scorer.py

License

MIT

Structural Note

This dataset identifies a measurable coupling pattern associated with systemic instability. The sample demonstrates the geometry. Production-scale data determines operational exposure.

What Production Deployment Enables

• 50K–1M row datasets calibrated to real operational patterns • Pair, triadic, and quad coupling analysis • Real-time coherence monitoring • Early warning before cascade events • Collapse surface and recovery window modeling • Integration and implementation support

Small samples reveal structure. Scale reveals consequence.

Enterprise & Research Collaboration

Clarus develops production-scale coherence monitoring infrastructure for critical systems across healthcare, finance, infrastructure, and regulatory domains.

For dataset expansion, custom coherence scorers, or deployment architecture: team@clarusinvariant.com

Instability is detectable. Governance determines whether it propagates.