ClarusC64/clinical-quad-serotonergic-dose-escalation-cyp-inh-alert-override-serotonin-tox-v0.1
What this repo does This dataset models serotonin toxicity risk under polypharmacy. It predicts when the interaction between serotonergic burden, rapid dose escalation, CYP inhibition, and interaction alert override behavior creates a high probability of a serotonin syndrome event. Core quad serotonergic_burden_index dose_escalation_index cyp_inhibition_index interaction_alert_override_index Prediction target label_serotonin_event Row structure Each row represents a patient prescribing risk… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-serotonergic-dose-escalation-cyp-inh-alert-override-serotonin-tox-v0.1.
What this repo does
This dataset models serotonin toxicity risk under polypharmacy. It predicts when the interaction between serotonergic burden, rapid dose escalation, CYP inhibition, and interaction alert override behavior creates a high probability of a serotonin syndrome event.
Core quad
serotonergicburdenindex doseescalationindex cypinhibitionindex interactionalertoverride_index
Prediction target
labelserotoninevent
Row structure
Each row represents a patient prescribing risk snapshot during medication changes. The model predicts whether the coupled serotonergic and governance conditions imply a serotonin toxicity 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.