Citation Readiness
The degree to which content is structured, authoritative, and clear enough to be cited by an AI model as a source in a generated answer.
This term is part of the 3LA EntityMap → /entitymap.html
Related terms
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.
Structural Proof Gap
metricA 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.
Citation Worthiness
metricA sub-score within L3 measuring whether content contains verifiable, well-sourced claims that AI models will trust and cite.
Chunk Optimization
coreStructuring content into self-contained units of 100–150 words where each section addresses one specific question - making it easy for AI models to extract, understand and cite the information.
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.
