The Boundary Generativity Test: An Exploratory Framework for Information Saturation

This white paper introduces the Boundary Generativity Test (BGT), an exploratory diagnostic framework for identifying a recurring characteristic time scale governing informational saturation in complex, non-equilibrium dissipative systems. We propose the existence of a Stochastic Decoherence Attractor at approximately 12.4 seconds, functioning as a macroscopic threshold where systems operating at peak informational capacity exhibit a non-linear spike in control-variable variance, termed the Inference Wall, while remaining within mechanical hardware limits. BGT metrics are applied across four illustrative case study domains. In autonomous systems, Grade A highway telemetry from the comma2k19 dataset identifies an Inference Wall at T plus 10.76 seconds and a saturation peak at T plus 12.40 seconds. In biological systems, re-analysis of the 2009 Berlin 200m World Record biomechanical splits reveals a functional regime shift near T plus 11.40 seconds consistent with ATP-CP depletion and the saturation threshold. In geophysical systems, an M7.7 seismic event off Japan in April 2026 yields a seismic-tsunami temporal delta of 2378.5 seconds, explored as a single-event numerical correspondence with the Harmonic Scaling Hypothesis. In financial systems, the May 2021 BTC/USD Flash Crash shows a liquidity variance shift at approximately T plus 14.93 minutes, numerically consistent with the sixth-order harmonic of the base resynchronization lag of approximately 14.0 seconds. A Harmonic Scaling Hypothesis is introduced to explore how the local Metric Lag might extend into macroscopic information displacements across orders of magnitude. Speculative extensions to deep-space electromagnetic decoupling, referred to as the T96 Cliff hypothesis, are included as clearly demarcated thought experiments intended to generate testable predictions for future missions. This white paper serves as the conceptual companion to a technical manuscript submitted to Physica A: Statistical Mechanics and its Applications, which presents the empirical and statistical core of the framework. The present document extends that work with additional case studies and speculative scaling hypotheses intended to guide future empirical investigation rather than to assert established physical laws. All results should be treated as exploratory and hypothesis-generating.