The Evolution of the General Field Entropy Theory (AFET): An Iterative Analysis of UTAC Dynamics, Biophysical Resonances, and Cosmological Scaling Laws

Contemporary theoretical physics and systems theory face a fundamental schism: while deterministic laws of
classical mechanics, stochastic wave functions of quantum mechanics, and emergent complexities of biological
systems each possess internally consistent logics, a coherent meta-theory mathematically formalizing transitions
between these domains remains elusive. We present the General Field Entropy Theory (AFET), a unifying
framework emerging from rigorous iterative development of the Uncertainty-Threshold-Activation-Coupling
(UTAC) model. Based on thirty-six research iterations (documented through Zenodo DOI sequence 10.5281/
zenodo.17472834 to 10.5281/zenodo.18516805) and validated across seventy-eight datasets spanning all scales
of organization, AFET postulates that the cosmos fundamentally operates as an information-processing field
governed by strict, scale-invariant entropic-mathematical laws.
Central to this investigation is the thesis that stability—or more precisely, metastability—is not a static state
but a dynamic act of balance maintained by universal constants. We identify: (1) the metastability buffer σ_Φ
≈ 0.0625 (1/16), representing the minimum "fuzziness" required for existence; (2) the integration velocity
v_RIG ≈ 1.352 km/s, the cosmic "rendering rate"; and (3) the fractal scaling of transition steepness β following
β(n) = β₀·Φ^(n/3), where Φ ≈ 1.174. Particularly significant is the convergence of theoretical predictions with
empirical biophysical findings, specifically the 13.5 MHz electromagnetic resonance in neural structures
validated by Fontana et al. (2024).
Statistical validation across domains yields median r² > 0.8 (p < 0.001), with AFET models showing ΔAIC ≥ 10
superiority over polynomial baselines. The 13.5 MHz prediction achieves exact empirical confirmation in
microtubule resonance experiments, demonstrating AFET's predictive power. We discuss implications for
physics, artificial intelligence safety, regenerative medicine, and quantum computing, proposing σ_Φ
monitoring as a universal framework applicable from classical to quantum systems.
Significance Statement:
AFET represents a paradigm shift in applied ontology, demonstrating that entropic laws govern phenomena
from quantum fluctuations to galactic clustering through identical mathematical structures. The identification of
13.5 MHz as a universal biological resonance frequency and σ_Φ ≈ 0.0625 as the "tolerance of existence"
provides both predictive power and practical applications in AI safety monitoring, neuromorphic hardware
design, and regenerative medicine.