The Co-Creative Harmonic Synthesis: A Formal Metric for Asymmetric Epistemic Reliability in Human-AI Composition

Modern formal research increasingly relies on the synthesis of human intellect and artificial intelligence (AI). However, while AI accelerates theoretical output, its inherent tendency to hallucinate introduces systemic epistemic risks, lacking a unified mathematical constraint to evaluate the reliability of such collaborative research. This study addresses this gap by formalizing a meta-methodological framework, defining the "Reliable Paper" (Rp) metric. The research methodology compounds specific human

skill sets (Si) across a product sequence to form a baseline "meta-paper" (Mp), which is subsequently evaluated against an AI hallucination penalty variable (A.IH). The results demonstrate the foundational equation Rp =∏S i=1(1+Si )max(1,A.IH)By utilizing a maximum function as a lower-bound floor, the equation resolves the infinity paradox, proving that when AI error is negligible, structural reliability scales purely in proportion to compounded human intellect. This theoretical metric is successfully instantiated as the underlying procedural methodology for a corpus of four distinct papers spanning game theory, set-theoretic defeaters, and modal epistemology. The study concludes that human-AI collaborative research can be mathematically bounded, transitioning AI integration from an unquantifiable epistemic vulnerability to a structurally verifiable asset in formal academic production.