3 papers
stat.AP2026
From Stochastic to Stable: Rank Stability and Structural Sufficiency in AI Visibility Measurement
Ronald Sielinski
AI visibility measurement is comparative: practitioners want to know which domains generative search engines cite most often and whether observed differences are large enough to su…
stat.AP2026
Quantifying Uncertainty in AI Visibility: A Statistical Framework for Generative Search Measurement
Ronald Sielinski
AI-powered answer engines are inherently non-deterministic: identical queries submitted at different times can produce different responses and cite different sources. Despite this…
stat.AP2025
The BAD Paradox: A Critical Assessment of the Belin/Ambrósio Deviation Model
Ronald Sielinski
The Belin/Ambrósio Deviation (BAD) model is a widely used diagnostic tool for detecting keratoconus and corneal ectasia. The input to the model is a set of z-score normalized …