CitationMapper Atom 1 — ChatGPT (AI Visibility & Prompt Competition Dataset)

CitationMapper™ White Paper & Research Dataset

CitationMapper™ is the first dedicated platform for measuring AI visibility and prompt competition across large language models (LLMs) such as ChatGPT, Gemini, Claude, and Perplexity. This record includes the official CitationMapper White Paper, supporting research materials (README, OVERVIEW, PROCESS, ROADMAP), and associated datasets published under the AIVO Standard™ framework.

The dataset provides:

The full CitationMapper White Paper outlining methodology, the Prompt Visibility Competition Score (PVCS™), and the Tier-1/2/3 citation stability framework.

Structured documentation of how prompts are tested across 65,000+ queries.

Industry-specific mapping of Tier-1 citation sources that drive LLM visibility.

Supporting process explanations, diagrams, and roadmaps for implementation.

Purpose:To establish a research-driven framework for AI visibility optimization, enabling organizations to measure, analyze, and strategically improve their presence in AI-generated responses.

This record forms part of the AIVO Mesh Lab publishing stream using the Micro Content Atom (MAS 1.0)specification.