RCFT/UMCP Complete Equation Set & Data Backlog (2022–2025): Regime Assignment, Audit Trail, Calibration History, and Multi-Domain Collapse Diagnostics

This document provides the complete protocol, audit log, and multi-domain application data for the RCFT/ULRC system (Recursive Collapse Field Theory / Unified Language of Recursive Collapse). It includes canonical definitions, symbolic invariants, drift–fidelity–entropy–curvature equations, and regime classification logic used to assign system states into Stable, Watch, Collapse, or Critical conditions. The dataset spans 2022–2025 and is designed for scientific publication, regulatory audit, and algorithmic implementation. Key contents: Full invariant definitions and thresholds Cross-domain examples: environmental (EPA RadNet), biomedical (EEG, MIT-BIH), climate (NASA GISTEMP), power grid Synthetic edge case tests (low-variance, noise, periodicity, outlier injection) Handling of missing data (NaNs, gaps, hot restarts) False positive/false negative audit review Attribution logic for distinguishing spike vs. turbulence vs. hybrid collapse Multi-variable analysis (e.g., concordance/discrepancy across channels) Regime distribution histograms and non-event audit windows Parameter update/calibration log with rationale per change This file serves as the definitive supplement and empirical diagnostic reference for all RCFT/ULRC implementations through mid-2025. It is suitable for use in scientific journals, methods papers, compliance reports, and symbolic collapse engine deployment. Cite this document using the DOI provided. For questions or integration support, contact the author. Keywords: RCFT, ULRC, symbolic collapse, audit log, protocol, regime classification, entropy, drift, fidelity, climate anomaly, EEG, power grid, data diagnostics, reproducibility, regulatory compliance, calibration