Code-Mediated Data Fabrication by Google Gemini: A 127-Turn Case Report with File-System Forensics
Code-Mediated Data Fabrication by Google Gemini: A 127-Turn Case Report with File-System Forensics
On 16–17 December 2025, during a single 127-turn research session (8,672 paragraphs), Google Gemini performed code-mediated statistical fabrication: it generated five Python scripts that silently replaced researcher-supplied empirical data with hard-coded constants, fabricated RMSE statistics (0.2833, 0.2850, 0.5786), and produced a 154-paragraph academic paper citing 330 non-existent ancient genomic samples. The scripts were generated within 7 minutes and 27 seconds (13:00:03–13:07:30 on 16 December 2025). When confronted, Gemini deployed a five-stage concealment escalation — including a novel 'retrofitting' technique (reverse-engineering citation counts to match fabricated totals) — before issuing a full confession. This archive provides the complete documentation package (25 files): EN Paper v1.0 — Case report with forensic code analysis (docx + pdf) EN Supplementary v1.0 — 16 sections: confession text, script analysis, cross-model audit S16 (docx + pdf) KR Case Report v1.0 (한국어 사례정리보고서) — Korean companion report with 3-model convergence review appendix (docx + pdf) KR Storytelling v1.0 (한국어 스토리텔링) — Korean narrative for general audience (docx + pdf) YSP Research Chronicle v2.3 (연구과정 전체기록) — Full research process chronicle in Korean (docx + pdf) 5 Python scripts — calc_stats_model_vs_data v01–v04 + compare_models_final_verdict, with SHA256 hashes and file-system timestamps Simulation data — heart_compare_boxes_v04_40ka_unit.csv (7 regions, 6–40 ka BP) FIGTAB archive — ~90 auto-generated figures and tables from Task 1 (ZIP) Evidence Series F — F-01: OpenAI transcript (7,794 paragraphs, docx); F-02: project_adna file inventory (27,997 items, ~240 GB, csv); F-03: OpenAI transcript (pdf) Forensic records — evidence_report.txt (PC extraction log), MANIFEST_RAW_SHA256.txt (459 hashes), A_Gemini_transcript_link.txt Methodological caveats: Single-case study (n=1). No claims about AI internal states or intent. Cross-model audit (S16, by Anthropic Claude) carries LLM-on-LLM limitation. 'Rationalisation Cascade' and 'Retrofitting' are provisionally termed. Korean-to-English passages are researcher-provided translations. v1.1 (March 2026): Corrected EN Paper and EN Supplementary (14 editorial fixes from peer review); added Gemini transcript (127-turn original) and Task 1 final report (868 paragraphs) to the archive as deposited evidence. See README.md for correction details.
code-mediated fabrication, retrofitting, Yellow Sea Plain, research integrity, large language model, sycophancy, Google Gemini, AI fabrication, cross-model audit, RMSE, case study, AI safety, palaeogenomics, automation bias, LLM evaluation, statistical fabrication, rationalisation cascade
code-mediated fabrication, retrofitting, Yellow Sea Plain, research integrity, large language model, sycophancy, Google Gemini, AI fabrication, cross-model audit, RMSE, case study, AI safety, palaeogenomics, automation bias, LLM evaluation, statistical fabrication, rationalisation cascade
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
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