ClarusC64/clinical-5node-ddi-buf-lag-cpl-drug-interaction-toxicity-v0.1
What this repo does This dataset models a drug interaction toxicity cascade by measuring when drug interaction pressure rises, physiologic buffer capacity erodes, clinical response lags, and care-team coupling tightens across prescribers, crossing a phase transition into an unrecoverable toxicity cascade state. Core quad ddibuflagcpl Prediction target label_cascade_state Row structure One row represents a clinical medication-risk… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-5node-ddi-buf-lag-cpl-drug-interaction-toxicity-v0.1.
What this repo does
This dataset models a drug interaction toxicity cascade by measuring when drug interaction pressure rises, physiologic buffer capacity erodes, clinical response lags, and care-team coupling tightens across prescribers, crossing a phase transition into an unrecoverable toxicity cascade state.
Core quad
ddi buf lag cpl
Prediction target
labelcascadestate
Row structure
One row represents a clinical medication-risk scenario with numeric signals for drug interaction pressure (ddi), buffer capacity (buf), governance/response lag (lag), and coupling tightness (cpl) across prescribers and care settings, paired with a binary cascade state label that marks the phase transition into drug interaction toxicity cascade conditions.
Files
data/train.csv data/tester.csv scorer.py
Evaluation
Run predictions on tester.csv. 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.