Developing a Canon-Constrained Expert System for Scientific Theory and Simulation Gold Standards, Human Oversight, and AI-Based Auditing

This article presents a methodological framework for developing scientific theories and simulations under artificial intelligence augmentation. It introduces a canon constrained expert system that combines a fixed versioned canon, explicit procedural instructions, non optional validation standards, open and machine readable documentation, and independent AI based audits. Using the Methane Metauniverse project as a case study, the work demonstrates how AI can accelerate exploration while remaining auditable, reproducible, and falsifiable. The contribution makes no physical claims and focuses instead on governing the research process itself. The proposed approach is transferable to any rule bound and logically constrained domain where AI assisted reasoning must remain accountable and free of conceptual drift.