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This document describes the Reflexive Epistemic Fabric, a technical framework for modelling an autonomous system's internal assumptions and dependencies as a runtime graph, enabling structural monitoring of reasoning integrity rather than output-only validation. It outlines how graph-based signals — including connectivity, topological complexity, non-orientable cycles, temporal decay, and assumption criticality — can be used to support deterministic safety responses, auditability, and evidentiary logging in safety-critical AI environments. The note serves as a prior art disclosure and conceptual and architectural record of the approach and its operational rationale, without exposing implementation-sensitive detail beyond what is necessary to explain the method.