fractional dynamical model estimation with unknown unknowns
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Updated
Sep 5, 2020 - Jupyter Notebook
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unknown-unknowns
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Theorem of the Unnameable [⧉/⧉ₛ] — Epistemological framework for binary information classification (Fixed Point/Fluctuating Point). Application to LLMs via 3-6-9 anti-loop matrix. Empirical validation: 5 models, 73% savings, zero hallucination on marked zones.
artificial-intelligence methodology uncertainty-quantification knowledge-representation autonomous-agents epistemology philosophy-of-science epistemic-logic json-protocol scientific-method epistemic-uncertainty unknown-unknowns large-language-models context-management token-optimization ai-interoperability hallucination-prevention
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Updated
Feb 1, 2026 - Python
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