ClarusC64/clinical-quad-basin-depth-intervention-timing-support-exposure-stability-recovery-window-v0.1
What this repo does This dataset models recovery surface formation in patient state dynamics. It predicts when the interaction between basin depth, intervention timing, support load, and exposure stability produces a recovery window where the patient is likely to return to a stable basin rather than remain trapped in a degraded regime. Core quad basin_depth_index intervention_timing_hr support_load_index exposure_stability_index Prediction target label_recovery_window Row structure Each row… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-basin-depth-intervention-timing-support-exposure-stability-recovery-window-v0.1.
What this repo does
This dataset models recovery surface formation in patient state dynamics. It predicts when the interaction between basin depth, intervention timing, support load, and exposure stability produces a recovery window where the patient is likely to return to a stable basin rather than remain trapped in a degraded regime.
Core quad
basindepthindex interventiontiminghr supportloadindex exposurestabilityindex
Prediction target
labelrecoverywindow
Row structure
Each row represents a post-event patient state snapshot. The model predicts whether the coupled stability indicators and timing conditions imply a recovery window within the next assessment interval.
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.