Introduces Signal-Native Papers (SNP), a bilateral document architecture in which every published work carries two co-equal expressions: the human-readable text and a machine-readable expression that describes the work's scope, entities, and retrieval boundaries in structured form. The architecture comprises thirteen elements organised in three tiers, derived from systematic analysis of seven predecessor approaches to machine-readable publishing. A Tier 1 proof of concept has been implemented. The full specification is maintained by AI Visibility Architecture Group Limited
Bernard Lynch (Sun,) studied this question.