Maya-Meta P2: A Self-Audit of Two Emergent Constants — The Buddhi S-Curve Is Formula-Determined and the Bhaya Quiescence Rate Is Not a Statistical Artifact

This paper performs a rigorous self-audit of two empirical constants reported across the Maya Research corpus, asking whether they reflect genuine emergent behaviour or are artifacts of mathematical construction or prior statistical conventions. Two direct experiments were conducted using real saved data from the Maya corpus to test whether the Buddhi S-Curve Determinism and the Bhaya Quiescence Law could be explained away by known alternative mechanisms. Free-parameter logistic fits on measured data yielded R²=0.149 (Samvad-P1, n=194) and per-stage R²=−0.227 to 0.079 (Vaidya-P2, n=84), confirming that the S-curve's perfect fit (R²=1.0000) is formula-determined and circular by construction, while a line-by-line audit across 26 substrates found zero three-sigma references in the Bhaya detection path, establishing that its proximity to Shewhart's 0.27% false-alarm rate is a coincidence of value rather than mechanism. Both constants are therefore reframed with greater precision: real monotonic consolidation progression exists in the data, and the Bhaya Quiescence Law (β*≤0.32%) reflects fear-neuron firing rate against a fixed threshold rather than any statistical test. This work forms part of the Maya-Meta Series, which synthesises and stress-tests empirical constants across the full Maya Research portfolio. Series: Maya-Meta Series — synthesis and confirmation of empirical constants across the full Maya Research portfolio. Bhaya Quiescence Law (β* ≤ 0.32%) and Buddhi S-Curve Determinism (R²=1.0000) confirmed across 19+ substrates. Links: GitHub Repository (private — to request access: email research@nexuslearninglabs.in with subject Code Access Request — Maya-Meta-P2.git and your research context) | Interactive Dashboard | FAQ | Full Series Index — venky2099.github.io Nexus Learning Labs, Bengaluru · UDYAM-KR-02-0122422 · BHASKAR IN-0526-9452JSORCID: 0000-0002-3315-7907 · VAIRAGYA_DECAY_RATE = 0.002315 (embedded in all canonical hyperparameters)Canary: MayaNexusVS2026NLL_Bengaluru_Narasimha