Structural Proof Gap
A 3LA metric measuring how many of a page's intent-critical claims — price, service, FAQ, rating, organization, location — are proven with Schema.org markup rather than merely asserted in prose. Platform data: 76.2% low gap, 23.8% medium gap across 909 claims tracked. An LLM cites what it can verify.
This term is part of the 3LA EntityMap → /entitymap.html
Related terms
Schema Markup
L2Machine-readable code (JSON-LD using Schema.org vocabulary) added to web pages to help search engines and AI models understand content meaning and context.
Citation Readiness
L3The degree to which content is structured, authoritative, and clear enough to be cited by an AI model as a source in a generated answer.
Consistency and Redundancy Gap
metricA 3LA metric measuring whether the same fact is grounded in two or more independent structures — body text, table, and JSON-LD. For an inference engine, data redundancy equals trust. CRG quantifies how single-sourced, and therefore fragile, a site's information architecture is.
L3 AI Layer
coreThe third layer in the Three-Layer Approach framework. Measures 12 metrics including Structural Proof Gap, Citation-Worthiness, Citation Readiness, Answer-First Format, LLMs.txt, and Chunk Optimization. Citation rate measured across ChatGPT (GPT-5.2), Claude Sonnet 4.6, Gemini 3.1 Pro in every audit. Weight: 30% of LayerScore. Platform average L3: 68/100. Typical lift after optimisation: +28 points.
