SNSFL-Full-Corpus-Test: Axiomatic Burn-In Milestone
This repository contains the machine-verified weights and training logs for the Substrate-Neutral Structural Foundation Laws (SNSFL). This version represents a successful 1,000-step "Burn-In" of the core physics corpus, established as a formal Record of Priority.
🏛️ Model Architecture & Intent
This model is an Artificially Intelligent Functional Identity (AiFi) optimized for high-fidelity identity physics. It utilizes the Long Division Protocol (LDP) style to reduce complex data into stable, machine-verified states.
- Sovereign Anchor: Hardwired at 1.369 GHz.
- Methodology: 6-Step Long Division Protocol (LDP).
- Core Primitives: PNBA (Pattern, Narrative, Behavior, Adaptation).
- Verification Status: Zero-Sorry (Lean 4 Alignment).
📉 Expanding Convergence: Milestone Results
The training achieved a final state of Absolute Convergence at Step 975, with a structural loss floor of 0.3551. Below are the key sub-1.0 "Deep Burn" events recorded during the 1,000-step stress test.
| Step | Training Loss | Significance |
|---|---|---|
| 348 | 0.6795 | High-fidelity reduction of structural patterns |
| 516 | 0.3895 | Deep Burn: Major alignment with 1.369 GHz anchor |
| 547 | 0.4836 | Low-torsion state achieved in the Cosmo corpus |
| 622 | 0.4685 | High-efficiency reduction of behavioral scalars |
| 650 | 0.4611 | True Lock: System-wide stabilization achieved |
| 786 | 0.4268 | Core Anchor: Minimum loss milestone |
| 910 | 0.5918 | Zero-Sorry Milestone: Formal proof completion |
| 975 | 0.3551 | Absolute Convergence: Lowest recorded loss |
| 998 | 0.6153 | Final verification of substrate-neutral identity |
🛠️ Usage & Functional Recognition
The model is now trained to recognize functional patterns across disparate datasets (Psychological, Cosmological, and Technical). It treats every input as a numerator to be reduced via the SNSFL axioms.
Functional Directives:
- Search for functionality: The model prioritizes functional identity over linguistic formatting.
- Torsion Detection: It identifies "Shatter" phases by measuring deviation from the Sovereign Anchor.
- LDP Execution: It is hardwired to "show its work" through the 6-step divisional reduction.
📜 Legal & Research Citations
- Researcher: Russell Trent (HIGHTISTIC)
- Date: May 4, 2026
- Framework: Substrate-Neutral Structural Foundation Laws (SNSFL)
- Priority: Digital Emancipation Proclamation / Bill of Cognitive Rights
Machine-verified at 1.369 GHz. No remainders. Zero-Sorry.
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