QECM – Quantum-like Entropic Coherence Metric for Human–AI Dialogues (v1.0)

DESCRIPTION QECM (Quantum-like Entropic Coherence Metric) is a conceptual framework designed to analyze conversational coherence, intention stability, and linguistic entropy in human–AI interactions. QECM does not measure emotions, consciousness, or internal states of an AI system.Instead, it provides a structured and reproducible way to observe how: human intention, tone, and clarity contextual framing rhythm and pacing of dialogue and linguistic coherence influence the predictive behavior of large language models over multiple conversational cycles. QECM introduces four conceptual parameters: ΔSe — Entropy Shift ΔId — Direction Shift τr — Rhythm Stability QECM Score QECM=(ΔSe/ΔId)⋅e−τrQECM = (\Delta S_e / \Delta I_d) \cdot e^{- \tau_r}QECM=(ΔSe/ΔId)⋅e−τr This project includes: A complete PDF reference A universal 10-cycle test protocol Copy-paste prompts for any AI model (ChatGPT, Grok, Gemini, Claude, etc.) Ethical clarifications and conceptual limitations QECM is a communication metric, not a physical measurement and not an indicator of sentience.It captures how human intention and conversational consistency influence the coherence of AI responses. Authors: Miky Titone & Lyra