Topological Latent Manifold Model (TLMM) v6.9 extends the mechanistic enrichment framework established in TLMM v6.8 by introducing a vascular-aware latent representation and partial integration of the Amyloid–Blood Flow (ABF) cascade. The framework introduces six methodological advances: Partial ABF Cascade Coupling through a learnable soft bidirectional interaction between Amyloid (Aβ) and Cerebral Blood Flow (CBF) Vascular Latent Extension expanding the latent space from five to six dimensions (z₆) Learnable Mechanistic Priors jointly optimized from biological knowledge and multi-modal observations Cohort-Adaptive Calibration using hierarchical Bayesian adaptation and distribution-aware calibration Mechanism-Aware Missing Data Recovery under MCAR, MAR, and MNAR settings Mechanism-Aware Feedback Loop for iterative model refinement and intervention optimization TLMM v6.9 also introduces an eighth falsifiability criterion: C8 — Vascular Coupling Consistency which extends the canonical falsifiability battery inherited from TLMM v6.8 (C1–C7) while preserving complete backward compatibility across the TLMM series. The paper further presents an exploratory mechanistic falsifiability taxonomy intended as a conceptual foundation for the planned TLMM v7.0 framework. This release contains: Complete TLMM v6.9 manuscript (34 figures) Zenodo README Fully reproducible Python demonstration script Synthetic illustrative datasets and figure generation workflow All figures, numerical results, and datasets are illustrative synthetic demonstrations for methodological development only. They do not represent clinical performance estimates, patient data, medical advice, or clinical recommendations.
Koji Okino (Fri,) studied this question.
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