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

Machines have axioms too. This chapter translates the axiom-stack framework into the synthetic domain, showing how AI systems have architectural bedrock, objective functions that function as values, and learned weights that function as worldview. It introduces instrumental convergence, the Stop Button Problem, and the terrifying logic of pure optimisation. No consciousness required—just cold, coherent goal‑seeking.