Appendix A provides Python code for NPF/CNI calculation (raw score, linear/sigmoid normalisation, CNI aggregation) and simulation parameters. Appendix B gives a decision tree for selecting the sigmoid steepness parameter k based on cultural context (individualist vs. collectivist), with sensitivity analysis guidance. Both are theoretical tools; no validation is claimed.

The Composite NPF Index (CNI) extends the Neural Pathway Fallacy to belief networks, quantifying systemic epistemic risk. This paper presents the CNI formula (weighted sum with normalised weights), normalisation methods (linear, sigmoid with cultural parametrisation), sampling adequacy, and a gradient‑descent weight update (hypothesis). It introduces the neurodiversity provision (autistic resistance to high‑SE NPFs) and positions CNI within the Fractal Entailment Network (FEN