Assesses AI citation rates based on content structure, suggesting implications for AI text generation.
Corrected version. E001 tested declarative vs narrative content structure on Perplexity, January 2026. Corrected result from reconstructed counts: 18/30 (60.0%) declarative vs 11/30 (36.7%) narrative, a 23.3pp gap, two-proportion p = 0.07, not significant at 0.05, clearing the lab's 22.0pp measured noise floor (E016) by 1.3 points. Exploratory 15-query baselines on ChatGPT (8/15 vs 5/15) and Gemini (9/15 vs 5/15) are directionally consistent and individually non-significant, reported here for the first time. Version 1's figures (n=75, 61% vs 37%, 24pp, p < 0.01) were transcribed from a write-up later found to contradict its own revision history and are withdrawn, along with v1's blinding, session structure, and session-variance claims, which have no surviving source. No raw data files exist. Full provenance in the paper.
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Artur Ferreira (2026) studied this question.
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