ClarusC64/clinical-quad-cyp-inhibition-induction-dose-density-exposure-volatility-safety-event-v0.1
What this repo does This dataset models safety event risk driven by CYP enzyme saturation and opposing metabolic forces. It predicts when the interaction between CYP inhibition, CYP induction, dose density, and exposure volatility produces a safety event. Core quad cyp_inhibition_index cyp_induction_index dose_density_index exposure_volatility_index Prediction target label_safety_event Row structure Each row represents a patient metabolism state snapshot during active therapy. The model… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-cyp-inhibition-induction-dose-density-exposure-volatility-safety-event-v0.1.
What this repo does
This dataset models safety event risk driven by CYP enzyme saturation and opposing metabolic forces. It predicts when the interaction between CYP inhibition, CYP induction, dose density, and exposure volatility produces a safety event.
Core quad
cypinhibitionindex cypinductionindex dosedensityindex exposurevolatilityindex
Prediction target
labelsafetyevent
Row structure
Each row represents a patient metabolism state snapshot during active therapy. The model predicts whether the coupled metabolic forces and exposure instability lead to a safety event within the next monitoring 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.