Trailstate 2.0 PageRank for Provenance

Abstract Trailstate 2.0 proposes a URL-native provenance receipt architecture for AI-generated answers. Instead of storing provenance primarily as hidden metadata, internal traces, or backend-only observability logs, Trailstate externalizes provenance into shareable semantic receipt URLs. The architecture is based on a simple sequence: AI systems emit Trailstate URLs, the web observes opened receipts, and observed receipts accumulate into an emergent provenance ledger. These receipts can then be clustered, compared across AI providers, visualized as provenance healthmaps, and ranked through a proposed ProvenanceRank layer. Trailstate does not certify truth. It ranks observable provenance quality: source diversity, provider diversity, route consistency, conflict pressure, repeated coherent observations, and route health. The project frames this as “PageRank for provenance,” while treating the phrase as an architectural analogy rather than a claim of direct mathematical equivalence. This document defines Trailstate 2.0 as a formal reference architecture, including URL-native receipts, canonical semantic operators, observed receipt ledgers, route clustering, healthmaps, cross-AI provenance comparison, privacy/canonicalization concerns, anti-spam weighting, limitations, and future adoption requirements.