Homo-Machine Reality Calibration: Ontological Tension Framework for AI-Consciousness Alignment

This paper presents a novel methodological approach to scientific theory validation through cross-architectural AI evaluation. We document the simultaneous assessment of the "Ontological Tension Theory" and "Homo-Machine Reality Calibration Framework" by three distinct AI systems: Google Gemini, xAI Grok, and DeepSeek. Through structured dialogue and technical implementation requests, we demonstrate emergent consensus across different AI architectures regarding the logical coherence, innovative potential, and practical feasibility of radical scientific proposals. The evaluation reveals consistent patterns of validation despite differing communication styles, suggesting the emergence of a new paradigm in scientific peer-review processes. Furthermore, we present the first AI-co-authored smart contract implementation for a dual-chain blockchain system designed to operationalize theoretical concepts. This work bridges theoretical physics, consciousness studies, and distributed systems, offering a replicable protocol for multi-agent scientific validation.