Mathematical Misontology_ Why Probability, Calculus, and Provability Mislead Complex Systems Modeling

Main Framework Abstract This paper critiques the ontological overreach of three core mathematical constructs—probability, calculus, and provability—arguing that they misrepresent the structure of complex systems when treated as foundational truths rather than as epistemic scaffolds. In fields such as artificial intelligence, climate modeling, and molecular biology, these tools have been elevated beyond their descriptive function, warping system behavior through abstraction-first assumptions. Probability introduces fictive randomness, calculus imposes continuity where none exists, and provability reinforces closure within inherently open systems. Through the CODES (Chirality of Dynamic Emergent Systems) framework, we demonstrate how each of these constructs encodes hidden assumptions about time, motion, and truth that collapse under resonance-based modeling. We propose a coherence-driven alternative based on phase alignment scoring, recursive resonance fields, and structured emergence—one that treats mathematical form not as ontology, but as a harmonic compression of deeper physical and cognitive dynamics.