Domain-Contextualized Inference: A Computable Graph Architecture for Explicit-Domain Reasoning

ArXi:2604.04344v1 Announce Type: new We establish a computation-substrate-agnostic inference architecture in which domain is an explicit first-class computational parameter. This produces domain-scoped pruning that reduces per-query search space from O(N) to O(N/K), substrate-independent execution over symbolic, neural, vector, and hybrid substrates, and transparent inference chains where every step carries its evaluative context. The contribution is architectural, not logical.