Declarative vs Narrative Content Structure and AI Citation Rate on Perplexity (GEO Lab Experiment E001)

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 0.01) were transcribed from a write-up later found to contradict its own revision history and are withdrawn, along with v1's blinding, session structure, and session-variance claims, which have no surviving source.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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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-24
DOI
https://doi.org/10.5281/zenodo.20687901
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Declarative vs Narrative Content Structure and AI Citation Rate on Perplexity (GEO Lab Experiment E001)

Artur Ferreira
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

Declarative vs Narrative Content Structure and AI Citation Rate on Perplexity (GEO Lab Experiment E001)

Artur Ferreira
article en

Abstract

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 0.01) were transcribed from a write-up later found to contradict its own revision history and are withdrawn, along with v1's blinding, session structure, and session-variance claims, which have no surviving source.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.

Zenodo (CERN European Organization for Nuclear Research)
Grantmakers for Effective Organizations (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 35%
Artificial Intelligence in Healthcare and Education
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Declarative vs Narrative Content Structure and AI Citation Rate on Perplexity (GEO Lab Experiment E001) — Artur Ferreira · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS