What question did this study set out to answer?

This work aims to develop a framework that prevents epistemic collapse in outputs from large language models (LLMs).

May 16, 2026Open Access

FyCore A Framework for Structural Suppression of Epistemic Collapse

Key Points

This work aims to develop a framework that prevents epistemic collapse in outputs from large language models (LLMs).
Introduced a structural, non-behavioral framework with three layers: Silicon Lens (observation), Thought Value (measurement), and Φ_Fy (evaluation).
Mathematical formulation and empirical validation conducted in a minimal toy environment.
Demonstrated the unified approach to epistemic closure using a logarithmic barrier, indicating absolute certainty is not mathematically valid.
Simulation results are confined to a controlled environment, not intended as evidence for real-world LLM performance.

Abstract

This record contains the academic demonstration package for the FyCore Research Programme, Papers I–III. FyCore proposes a structural, non-behavioral framework for suppressing epistemic collapse in large language model outputs. The package includes the main framework paper, mathematical formulation, empirical validation under a minimal toy environment, companion notes, and reproducibility artefacts. The trilogy introduces three layers — Silicon Lens (observation), Thought Value (measurement), and ΦFy (constrained evaluation) — unified by a logarithmic barrier on epistemic closure that makes absolute certainty mathematically inadmissible. This work is explicitly scoped as an academic and demonstrative research package. It does not constitute a certification authority, runtime decision system, production validator, consciousness model, ground-truth oracle, or operational deployment claim. Simulation results are confined to a controlled toy environment and should not be interpreted as evidence of real-world LLM performance under production conditions. Scholarly circulation is open. Commercial operation, product integration, model-governance integration, certification use, or commercial runtime use requires a separate written license agreement with the author. Foundational preceding work: CCFy — A Curvature-Based Perspective on Regulatory Dynamics in Conscious Experience (Zenodo DOI: 10. 5281/zenodo. 18130127).

FyCore A Framework for Structural Suppression of Epistemic Collapse

Key Points

Abstract

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