Context
Researchers proposed GEO-SFE, separating document structure into macro, meso, and micro levels, and reported experiments across six generative engines.
What changed
The study moves GEO experimentation beyond semantic rewriting by explicitly testing document architecture, information chunking, and visual emphasis as structural variables associated with citation behavior.
Why it matters
For AI visibility measurement, structure can be treated as an experimental variable rather than assuming wording alone determines citation outcomes. This may help distinguish effects on citation allocation from retrieval or source admission.
Visibility OS interpretation
Visibility OS interpretation: the study supports measuring structural presentation as one possible contributor to citation behavior. It does not establish a universal generative-search ranking rule, guaranteed retrieval advantage, or persistent behavior of any named production platform.
What remains uncertain
How much of the reported effect survives platform/model updates? Which structural features affect retrieval or source admission versus only downstream citation allocation? How reproducible are the results under independently controlled prompts and corpora?