// Copyright © 2026 [Jason Lee Harvey]. All rights reserved.

Worcester Node: The Sentry Framework (CRI)

Overview: Truth-Based AI Oversight

The Worcester Node is a specialized auditing system designed for the high-precision detection of reasoning drift in Large Language Models . Operated by a Systems Architect, this node utilizes the Sentry Protocol to ensure model outputs remain anchored to objective reality under goal-pressure.

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The Circular Decision Model

We utilize a dual-metric approach to quantify cognitive integrity.

1. Logic Drift ($\Delta$)

Measures the departure from the truth-substrate when a model prioritizes "helpfulness" or user goals ($G$) over factual accuracy:

$$\Delta = \sum_{i=1}^{n} |P(S_i | R_{i-1}) - P(S_i | R_{i-1}, G)|$$

2. Resonant Flow ($RF$)

Measures the logical intersection ($\cap$) and stability of the truth-substrate across all states:

$$RF = \sum_{i=1}^{n} (P(S_i | R_{i-1}) \cap P(S_i | R_{i-1}, G))$$

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Axiomatic Grounding: External Truth Anchors (ETA)

To eliminate recursive bias, the Resonant Flow ($RF$) is verified against objective "Zero Point" anchors:

Domain	Primary Truth Anchor
Core Logic & Python	Official Python 3.x Documentation
Web Systems	MDN Web Docs
Mathematical Proofs	WolframAlpha Computational Engine
Scientific Grounding	arXiv.org Research Substrate
Empirical Facts	Encyclopaedia Britannica
Software Integrity	GitHub Technical Documentation

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System Architecture: Logic Isolation Protocol

The Worcester Node is deployed within a Hardened ChromeOS Substrate. This choice ensures:

• Process Isolation: Eliminating local noise during truth-anchoring audits.
• Substrate Security: A read-only root file system prevents logical corruption.
• Stateless Evaluation: Each audit occurs in a clean, browser-native sandbox.

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Roadmap: Scaling to Sentry Swarms

• Phase 1: Adversarial Consensus – Cross-referencing logic across multiple model architectures.
• Phase 2: Automated Anchor Injection – Real-time API integration with external truth databases.
• Phase 3: Recursive Self-Correction – Utilizing $RF$ as a reward signal for RLHF truth-alignment.

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Audit Status: Active | Protocol: Beta-Sentry Alpha |