Ω Collapse-Risk Functional Reference Implementation (Paper-Aligned Precomputed Label Mode) for Multi-Flow Healthcare System Collapse Prediction

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Authors: Hiroaki Aizawa
Cited by: 0

Abstract

Boundary note (added 2026-07-23): the Ω-centered empirical layer was self-retracted on 2026-05-31. Ω-centered validation is not currently supported as the active empirical basis; this record remains a historical, fixed, Ω-centered record and must not be cited as current validation. See the VOT Empirical Layer Boundary Note — https://doi.org/10.5281/zenodo.20474232. A later four-dataset head-to-head found that order gated by critical slowing does not beat free-energy signals (10.5281/zenodo.21422215, negative result). This software provides a deterministic reference implementation of the Ω (Omega) collapse-risk functional for multi-flow healthcare system collapse prediction. The implementation is aligned with the empirical evaluation framework introduced in: Empirical Evaluation of Ω as a Multi-Flow Collapse Predictor in Healthcare System Dynamics DOI: 10.5281/zenodo.18611100 and its subsequent multi-year replication study. This repository reproduces the evaluation pipeline using precomputed collapse-event labels (y_*), ensuring strict consistency with the published methodology. Implemented Components: • Intersection coverage panel evaluation protocol • Collapse event definition using percentile-based thresholds and persistence criteria • Multi-flow Ω predictor construction • Utilization-only baseline comparison • Leave-One-Region-Out (LORO) cross-validation • Optional temporal block validation • Deterministic reproducibility-oriented output generation IMPORTANT SCOPE NOTE: This software assumes an already constructed intersection coverage panel dataset (nhs_panel.csv). It does not reconstruct raw NHS data sources. Its purpose is to provide an evaluation-aligned reproducibility implementation of the Ω collapse-risk functional. Primary Purpose: Reproducible scientific validation and methodological reference implementation for Ω-based collapse-risk modeling in complex healthcare system dynamics. This repository is intended as a methodological reference rather than a production clinical decision tool.

Fields of Study & Subjects

Ecosystem dynamics and resilience Complex Systems and Dynamics Artificial Intelligence in Healthcare

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
12 February 2026
Language
EN