Noise Decorrelation as a Hypothetical Mechanism for Phase-Specific Neurometabolic Outcomes in HIV Infection — Code and Data Repository

Bayesian analysis code, curated neuroimaging datasets, and full reproducibility suite for "Noise Decorrelation as a Hypothetical Mechanism for Phase-Specific Neurometabolic Outcomes in HIV Infection." Implements a 5-model comparison framework using PyMC to test whether environmental noise correlation length (ξ) distinguishes preserved from vulnerable neurometabolic states during acute and chronic HIV infection. Includes hierarchical Bayesian inference across 44 individual trajectories, enzyme kinetics modeling, Tegmark-scale decoherence baselines, and WAIC/LOO model comparison. All manuscript figures and statistical results are reproducible from a single command. https://doi.org/10.64898/2026.02.10.703895