A Prototype Five-Axis Meta-Evaluation Interface for AI Responses: From Recursive Meta-Dialogue and Cross-Model Structural Analysis to Human-Centered AI Evaluation

This document is a follow-up research note to two previously published Zenodo records. The first record documented a recursive meta-dialogue with Claude concerning historical cyclicality, transformation, self-referential reasoning, and recursive dialogue structures. The second record examined the same Claude dialogue through ChatGPT-based structural analysis, comparing the generative styles, ethical boundaries, and self-understanding of Claude and ChatGPT. The present document extends these prior records into a practical interface proposal for AI response evaluation. Rather than treating AI-generated outputs as self-evidently reliable, it proposes a five-axis meta-evaluation UI intended to help users examine the assumptions, verifiability, uncertainty, overextension, and contextual bias embedded in AI responses. The proposed five axes are integrity, verifiability, deepening rate, premise transparency, and asymmetry correction. These axes are not intended to automatically determine the truth or falsity of AI-generated responses. Rather, they are intended as an auxiliary evaluation layer to support critical human judgment. This document should be understood as a prototype design note, not as a completed evaluation system. Future work should test the framework across multiple models, users, and task domains to evaluate its usefulness for AI literacy, hallucination detection support, and human-centered AI response evaluation.