UEDP v4 — Integrated Configuration & Attractor Discovery Engine

Detects configurational attractors — clusters of parameters locked into the same emergent regime — revealing what raw data alone cannot show. Based on the UEMK discovery (genomics validation) and financial factor stratification (Mkt-RF near Ω_crit = 1/e). All coupling detection is calculation-based (pairwise similarity of deviation percentages). Labels are dynamically derived — custom parameters are flagged explicitly when no domain match exists. Full 35-step protocol trace with clinical interpretation layer.

DOI: dx.doi.org/10.17504/protocols.io.14egnr5yml5d/v4 Ω_crit = 1/e ≈ 0.3679 · METP variational principle Full 35-step trace · Attractor detection · Fragility index Ramesh Kumar G S · Hidden Pointz Consulting, Bengaluru

Session Information

Parameter Entry

nearest-boundary deviation BIC Configuration Discovery Attractor Coupling · Fragility Index Regime Stratification
Unified Clinical Severity Model — Nearest Boundary Calculation:
• Deviation measured from nearest boundary (lower OR upper reference limit), NOT from midpoint.
• 1 clinical phase = 36.79% (1/e ≈ 0.3679) of the normal range.
• Phases = (Deviation % of Range) / 36.79
• Asymmetric weighting: Low and high deviations have different clinical multipliers.
• Non-linear scaling: Mild deviations (0-30% of range) count less; severe deviations count more.
• Total Severity (Ω) = e(-total_phases) — system coherence on a 0→1 scale.
• Critical threshold: Ω_crit = 1/e ≈ 0.3679 — below this = emergent/critical state.
Parameter Name Measured Value Lower Ref. Upper Ref. Deviation From % of Range Phases (÷0.3679)
O_obs = TAB = mean|z| — Total Abnormality Burden