ClarusC64/clinical-5node-sedation-buf-lag-cpl-procedural-sedation-resp-suppression-v0.1

What this repo does

This dataset models a procedural sedation respiratory suppression cascade by measuring when sedation pressure rises, respiratory buffer capacity erodes, monitoring and escalation lags increase, and cross-team coupling tightens across procedure settings, crossing a phase transition into an unrecoverable respiratory suppression cascade state.

Core quad

sedation buf lag cpl

Prediction target

labelcascadestate

Row structure

One row represents a procedural sedation scenario with numeric signals for sedation pressure (sedation), physiologic buffer (buf), monitoring/escalation lag (lag), and coupling tightness (cpl) across procedural teams and escalation pathways, paired with a binary cascade state label marking lock-in 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.