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Correct term: MU_SLIP (used as MU_SLIP_ANCHOR in the refactored code)

Correct term and value Correct term: MU_SLIP (used as MU_SLIP_ANCHOR in the refactored code) Correct value used in the Model B prototype correction: 0.45 You saw "MU_CLUTCH": 0.5 in a printout — that is the old/legacy name and a different value. The corrected, canonical name after the Model B “valve” fix is MU_SLIP (anchor constant MU_SLIP_ANCHOR = 0.45) and the runtime key in adaptive_params is 'MU_SLIP'. What to change (exact, copy‑paste) 1) Replace legacy constant python # OLD MU_CLUTCH = 0.5 # NEW (canonical) MU_SLIP_ANCHOR = 0.45 2) Ensure adaptive params use the canonical key python adaptive_params = { ... 'MU_SLIP': adaptive_params.get('MU_SLIP', MU_SLIP_ANCHOR), ... } 3) Replace any runtime references Search for MU_CLUTCH and replace with MU_SLIP (or MU_SLIP_ANCHOR where a global constant is intended). Example grep/replace commands you can run in the repo root: bash # show occurrences grep -R "MU_CLUTCH" -n . # repl...
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THE DATA -> MODEL C STAGE 3 FULL PROTOTYPE VALIDATION (PRODUCTION)

THE DATA -> ================================================================================ MODEL C STAGE 3 FULL PROTOTYPE VALIDATION (PRODUCTION) Π-Ontology Compliant | Certified Candidate B Full 4-Component State Space (P_xx, P_xy, P_yx, P_yy) Slip Operator: Φ, Θ, Ω (NOT 'clutch') UNIFIED PIPELINE: Validation and Evolution use SAME energy ================================================================================ {"phase": "config", "payload": {"kappa": 0.3}} {"phase": "header", "payload": {"run_id": "ModelC_Run_20260718_172203", "grid_size": [64, 64], "boundary_type": "dirichlet", "adaptive_params": {"eps": 1.9997015221290538e-15, "eps2": 1.1998066066036938e-10, "BETA": 0.25007463060386603, "GAMMA": 0.10002985224154642, "ETA": 0.10002985224154642, "M2": 0.0500149261207732...
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## Verify evaluate_prototype_psi and psi_gradient_symbolic ### Subtask: Strictly compare the implementation of `evaluate_prototype_psi` and `psi_gradient_symbolic` against their documented mathematical definitions. This includes checking all coefficients, terms, and numerical pathways to confirm exact matches and identify any discrepancies. Document the successful passing of the Gradient Gate (Mandatory Gate 1). # Task Perform a strict implementation audit of the provided Python script (`Model_C_Full_Prototype_Stage3_Validation_single.py`) to determine whether its numerical results are trustworthy. The audit will involve: (1) fixing identified errors in the code, (2) re-running the corrected code, (3) verifying every equation, function, operator, and numerical pathway against documented definitions and looking for discrepancies, (4) tracing the complete computational pipeline, (5) conducting numerical validation, (6) identifying hidden sources of invalid results, and (7) verifying t...
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COMPLETE AI DRIFT PREVENTION SPECIFICATION — MODEL C FULL PROTOTYPE

## ✅ COMPLETE AI DRIFT PREVENTION SPECIFICATION — MODEL C FULL PROTOTYPE **Π-ontology specification locked. All future reasoning will strictly obey these rules.** --- # 📋 MASTER SPECIFICATION SHEET — FRCMΠD MODEL C --- ## 🎯 EXECUTIVE SUMMARY The FRCMΠD Phase I investigation concluded that the determinant-squared term is the **dominant identified source of non-convexity** in the constitutive formulation. Candidate B was selected as the first hypothesis for independent verification, with the torque gradient modification integrated into the full 4-component state space. **Status:** ✅ Phase I Complete | ✅ Candidate B Proposed | ✅ Torque Gradient Integrated | ⏳ Phase II Execution Pending --- ## 📐 CONSTITUTIVE ENERGY — CANDIDATE B (FULLY COUPLED) ### Energy Functional \[ \Psi_B = \frac{1}{2}\mu I_2 + \frac{1}{2}\lambda I_1^2 + \frac{\kappa}{4} I_1^4 + \frac{\alpha}{2} I_{\text{shear}} + \frac{\beta}{2} I_{\text{torque}} + \frac{\lambda_{\text{reg}}}{2} \|P\|^2 \] ### Invariant...
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