# Bibliography for synthesis-fact-checking v2.0

**Purpose.** Source list for every empirical, journalistic, and methodological claim referenced in v2.0 SKILL.md, the C1-* protocols (`detailed-protocols.md`), per-family hallucination signatures, the citation-laundering-detection protocol, and the 2025-2026 production-incident archive. Each entry carries an explicit verification status.

**Labels.** **V** (Verified at expansion: fetched 2026-05-18, details and key numbers checked). **W** (Web-verified: methodology or organizational page; existence and broad framing confirmed). **C** (Cited only `[unverified at expansion]`: referenced by one or more of seven deep-research deliverables (Manus AI, Perplexity, Grok, ChatGPT, Gemini, DeepSeek, Claude exec) plus Claude Opus expansion, but not independently fetched; multi-contributor convergence raises the prior). **U** (Unreachable: searched and not located; retained so future maintainers know not to rely on it).

**Em-dashes.** Zero, per criteria 11 and 42 of the companion synthesis-content-quality skill.

**Anchor convention.** C1-* references protocols in `detailed-protocols.md` (NESTED, PARAPH, COMPOSITE, POSSHIFT, TRANS, URLROT, SYNTH, LAUNDER, TOOLHALL). C2-4a through C2-4g references refreshed common error patterns. Per-family signatures use `FAMILY-NN` (CLAUDE, GPT, GEMINI, DEEPSEEK, LLAMA, GROK).

---

## 1. Academic papers on hallucination, citation accuracy, and RAG fidelity

### 1.1 Verified at expansion

1. **Sharma, M. et al. (2023).** "Towards Understanding Sycophancy in Language Models." arXiv:2310.13548. **V.** Sycophancy in five production assistants; RLHF as structural driver. [C1-TOOLHALL, per-family sycophancy]

### 1.2 Cited in unified bucket, not independently verified

2. **Rao, D., Wong, E., Callison-Burch, C. (2026).** "Detecting and Correcting Reference Hallucinations in Commercial LLMs and Deep Research Agents." arXiv:2604.03173. **C.** 3 to 13 percent hallucinated and 5 to 18 percent non-resolving URLs across families; 13.3 percent Gemini deep-research-mode rate; ALL non-resolving GPT URLs hallucinated; provenance of the `urlhealth` tool. [C1-URLROT, C1-TOOLHALL GPT URL and Gemini mode split, C2-4f]

3. **Topaz, M. et al. (May 2026).** Lancet letter on fabricated citations in academic literature. STAT News coverage 2026-05-06. **C.** 1 in 277 PubMed papers in 2026 referenced a fabricated paper; sixfold rise 2023 to 2025 (Lancet framing) or twelvefold rise from 2023 (Claude exec framing, includes 2026 data). Verification flagged: Lancet venue, framing reconciliation. [C1-SYNTH, C1-LAUNDER, production-incident archive]

4. **"Retrieval Collapse."** arXiv:2602.16136. **C.** 67 percent pool contamination yields 80 percent exposure contamination in RAG. Verification flagged: arxiv prefix unusual for 2026. [C1-SYNTH, C1-LAUNDER]

5. **Walters, W. H., Wilder, E. I. (2023).** "Fabrication and errors in the bibliographic citations generated by ChatGPT." Scientific Reports 13: 14045. **C.** GPT-3.5 / GPT-4 hallucinated citation baseline. [C2-4f, C1-TOOLHALL GPT URL]

6. **Chelli, M. et al. (2024).** "Hallucination Rates and Reference Accuracy of ChatGPT and Bard for Systematic Reviews." JMIR Medical Education. **C.** GPT-4o 56 percent citation-error rate. [C2-4f, C1-TOOLHALL GPT URL, production-incident archive]

7. **Buchanan, J., Hill, S., Shapoval, O. (2024).** "ChatGPT Hallucinates Non-existent Citations: Evidence from Economics." Sage. **C.** [C2-4f, C1-TOOLHALL]

8. **Dahl, M. et al. (2024).** "Hallucinating Law." Legal-AI domain hallucination 58 to 88 percent. **C.** Via Penn 2026 and Perplexity. [C1-SYNTH, C1-URLROT, C2-4f, production-incident archive]

9. **Mugaanyi, K. et al. (2024).** DOI hallucination rates by discipline. Humanities 89.4 percent vs. natural sciences 29.1 percent. **C.** Via Penn 2026 and Perplexity. [C2-4f, C1-TOOLHALL CLAUDE-DOI]

10. **Magesh, V. et al. / Stanford RegLab (June 2024).** "Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools." 17 to 33 percent legal-AI hallucination with RAG. **C.** Verification flagged for specific percentages. [C1-URLROT, C1-SYNTH, C2-4f]

11. **Spennemann (2025).** arXiv:2504.08755. 30 to 40 percent of active web pages with AI signatures. **C.** [C1-SYNTH, C1-LAUNDER]

12. **Koenecke, A. et al. (2024).** Whisper mistranscription study. **C.** [C1-TRANS transcription-class hazard]

13. **Liang, W. et al. (2023).** "GPT detectors are biased against non-native English writers." arXiv:2304.02819. **C.** ESL safe-harbor cornerstone; ensures translation-drift detection does not over-fire on non-native prose. [C1-TRANS, C1-PARAPH]

14. **Kobak, D. et al. (2024).** "Delving into LLM-assisted writing in biomedical publications through excess vocabulary." arXiv:2406.07016. **C.** 13.5 percent of 2024 biomedical abstracts LLM-processed. [C1-SYNTH academic contamination]

15. **RIKER benchmark (2026).** arXiv:2603.08274. **C.** Long-context Llama fabrication above approximately 32K tokens. Verification flagged: threshold approximate. [C1-TOOLHALL LLAMA-LONGCONTEXT]

16. **Pew Research Center (2024).** "When Online Content Disappears." **C.** 25 percent of 2013-2023 webpages have disappeared. [C1-URLROT]

17. **Zittrain, J. et al. (2014).** Harvard Law Review link-rot study. **C.** 70+ percent of cited URLs no longer resolve. [C1-URLROT historical baseline]

18. **Sadatmoosavi.** Aslib 2026 link-rot study. **C.** [C1-URLROT]

19. **Hamdi (2025).** Sage Open. **C.** [C2-4f]

20. **Wallat (2024).** arXiv:2412.18004. **C.** [C2-4f, C1-TOOLHALL]

21. **"The Last Fingerprint: How Markdown Training Shapes LLM Prose."** arXiv:2603.27006. **C.** Numeric-prefix caveat (unusual for 2026). [C1-TOOLHALL]

22. **"The Rise of Verbal Tics in Large Language Models."** arXiv:2604.19139. **C.** [C1-TOOLHALL per-family signatures]

23. **"Preregistered Belief Revision Contracts."** arXiv:2604.15558. **C.** [C1-POSSHIFT]

24. **"How unique are hallucinated citations offered by generative AI models?"** arXiv:2604.16407. **C.** [C2-4f, C1-TOOLHALL]

25. **Shaib, C. et al. (2025).** "Measuring AI 'Slop' in Text." arXiv:2509.19163. **C.** Slop taxonomy; separates slop from fabrication. [C1-SYNTH framing]

26. **"When Thinking Fails: The Pitfalls of Reasoning for Instruction-Following in LLMs."** Amazon Science (NeurIPS 2025). **C.** [C1-TOOLHALL reasoning-mode fabrication amplifier]

### 1.3 Benchmarks

27. **HaluEval.** **C.** [C1-TOOLHALL cross-family rates]

28. **FActScore.** **C.** Atomic decomposition of factual claims; informs claim-extraction methodology. [SKILL.md section 1, C1-PARAPH]

29. **RAGTruth.** **C.** [C1-URLROT, C1-SYNTH RAG-mode evaluation]

30. **FaithBench.** arXiv:2410.13210. **C.** [C1-PARAPH, C2-4a]

31. **Vectara HHEM leaderboard.** **C.** [C1-TOOLHALL]

32. **HalluLens.** ACL 2025. **C.** [C1-TOOLHALL]

33. **AA-Omniscience.** **C.** [C1-TOOLHALL]

34. **Google FACTS benchmark.** **C.** Cited by ChatGPT input. [C1-TOOLHALL Gemini mode split]

35. **AI Multiple (January 2026).** "Hallucination Benchmark: 37 LLMs." 15 to 52 percent rates across 37 models. **C.** Via Perplexity (LinkedIn summary, Mark Hyman 2026-01-22). [C1-TOOLHALL]

36. **Enago (2025).** "AI Hallucinations in Research: Why 40 Percent of AI Citations Are Wrong." **C.** Only 26.5 percent of AI-generated academic references are entirely correct. [C2-4f, C1-SYNTH, C1-LAUNDER]

---

## 2. Journalism integrity organizations and methodology pages

37. **Poynter Institute.** https://www.poynter.org/. **W.** [C1-NESTED, C1-COMPOSITE, C1-POSSHIFT, SKILL.md section 5]

38. **Reuters Institute for the Study of Journalism.** https://reutersinstitute.politics.ox.ac.uk/. **W.** [C1-NESTED, C1-TRANS, C1-COMPOSITE]

39. **Nieman Lab.** https://www.niemanlab.org/. **W.** [C1-NESTED, C1-PARAPH, C1-POSSHIFT]

40. **PolitiFact methodology.** https://www.politifact.com/article/2018/feb/12/principles-truth-o-meter-politifacts-methodology-i/. **W.** [SKILL.md section 4, C1-LAUNDER]

41. **Snopes methodology.** https://www.snopes.com/transparency/. **W.** [SKILL.md section 4, C1-LAUNDER]

42. **Full Fact methodology.** https://fullfact.org/about/our-impartiality/. **W.** [SKILL.md section 4, C1-LAUNDER]

43. **Retraction Watch.** https://retractionwatch.com/. **W.** Database of retracted scientific papers. [SKILL.md section 6, C1-SYNTH, production-incident archive]

44. **Pulitzer Center (2025).** "Toward AI-Powered Source Audits." **C.** [C1-NESTED, C1-COMPOSITE]

45. **Claritybot.io (2026).** "AI Verification for Journalism." **C.** MIT 34 percent confidence-amplification finding referenced under C2-4c. [C1-NESTED, C1-PARAPH, C1-COMPOSITE, C1-POSSHIFT]

46. **MediaWise (Poynter).** **W.** [C1-NESTED, C1-COMPOSITE]

47. **UNC Charlotte Library (2025).** "AI Hallucinated Citations." **C.** [C2-4f, C1-SYNTH]

48. **VCU Library (2023).** "How to Fact Check Generative AI." **C.** [C1-PARAPH]

49. **TAMUCC Library (2023).** "Fact-checking AI with Lateral Reading." **C.** [C1-NESTED, C1-LAUNDER]

50. **CNTI Global AI and Journalism (November 2025).** **C.** [C1-NESTED, C1-COMPOSITE]

51. **HKS Misinformation Review.** **C.** [C1-LAUNDER citation cascade research]

52. **Tow Center / Columbia Journalism Review (March 2025).** "AI Search Has a Citation Problem." **C.** [C1-URLROT, C1-SYNTH, C1-LAUNDER]

---

## 3. Production incident sources (2025-2026 cases)

All entries in this section anchor to `production-incident-archive.md` by default; per-entry anchors below list the additional C1-* and C2-* protocols each case illustrates.

53. **Mata v. Avianca (2023).** S.D.N.Y. attorney sanctioned for AI-generated legal brief with fabricated citations. **W.** Legal-consequence baseline. [C2-4f]

54. **Mostafavi sanction (2025).** $10,000 sanction per Claude exec. CalMatters September 2025 coverage. **C.** Multiple Mostafavi cases exist; disambiguation flagged. [C2-4f, C1-SYNTH]

55. **Goldberg Segalla sanction (CHA, December 2025).** $60,000 sanction per Claude exec. **C.** Verification flagged for dollar amount and case caption. [C2-4f, C1-SYNTH]

56. **Damien Charlotin AI Hallucination Cases Database.** Over 1,455 sanctioned legal cases with AI-fabricated citations as of 2025. **C.** Database existence flagged. [C2-4f, C1-SYNTH, C1-LAUNDER]

57. **Chicago Sun-Times summer reading list (May 2025).** Multiple non-existent books with plausible titles by real authors. NPR May 2025 coverage. **C.** Cross-validated across Manus AI, Perplexity, ChatGPT, Gemini, DeepSeek inputs. [C2-4f, C1-SYNTH canonical example]

58. **Springer "Mastering Machine Learning" book retraction (April 2025).** Two-thirds fabricated references. Retraction Watch coverage. **C.** Cross-validated. [C2-4f, C1-SYNTH canonical academic-publishing example]

59. **BBC/EBU News Integrity report (October 2025).** 45 percent significant-issues rate. **C.** [C1-PARAPH, C1-POSSHIFT, C2-4a]

60. **Tsinghua ICLR paper retraction (2025).** Withdrawn after AI-generated references identified. **C.** [C2-4f, C1-SYNTH]

61. **MAHA Report (2025).** White House chronic disease report with AI-generated citations. **C.** [C1-SYNTH]

62. **Nieman Lab Margaux Blanchard / Victoria Goldiee (February 2026).** Synthetic-byline contamination. **C.** [C1-SYNTH]

63. **Megalopolis trailer controversy.** Fabricated or misattributed critic quotes in marketing material. **C.** [C2-4e, C1-COMPOSITE]

64. **Washington Post AI-generated podcast scripts (2026).** Fabricated and misattributed quotations in production testing. **C.** [C2-4e, C1-COMPOSITE, C1-NESTED]

65. **Google AI Overviews 2025 year-bug.** Wrong-year framing of historical events. **C.** Canonical C2-4a example.

66. **Mashable (2026).** "Grok 4 uses Elon Musk's X posts as a source." **C.** [C1-TOOLHALL, GROK-PLATFORM-BIAS]

---

## 4. Tool methodology pages and detector documentation

67. **Pangram Labs technical report.** "Pangram: AI-Generated Text Detection with Hard Negative Mining." arXiv:2402.14873. **C.** Hard-negative mining informs ESL safe-harbor. [C1-TRANS ESL caveat]

68. **GPTZero methodology.** https://gptzero.me/. **W.** [C1-TOOLHALL, cross-reference to content-quality v4.0]

69. **Originality.ai detector documentation.** https://originality.ai/. **W.** [C1-TOOLHALL]

70. **Copyleaks (2025).** "DeepSeek stylometric classification." DeepSeek output classified as OpenAI-like. **W.** [C1-TOOLHALL DEEPSEEK-LANGUAGE-MIXING]

71. **urlhealth (Rao et al., 2026).** Open-source pip-installable Python tool. Classifies URLs as LIVE, DEAD, LIKELY_HALLUCINATED, or UNKNOWN. **C.** [C1-URLROT recommended tool, citation-laundering-detection protocol]

72. **Anthropic Transparency Hub and System Cards.** https://www.anthropic.com/transparency. **W.** [C1-TOOLHALL Claude, CLAUDE-DOI-FABRICATION]

73. **GLEIF (Global Legal Entity Identifier Foundation).** https://www.gleif.org/. **W.** Recommended organization-name verification registry. [C2-4d]

74. **ORCID.** https://orcid.org/. **W.** Recommended researcher-identity verification registry. [C1-LAUNDER primary-author verification, C1-SYNTH synthetic-author detection]

---

## 5. Synthesis project internal cross-references

Paths below are relative to the author's workspace root — the directory
that holds these project checkouts.

Bucket paths share the prefix `ai-knowledge-rajiv/projects/synthesis-quality-skills-upgrade/resources/artifacts/`. Abbreviated as `<bucket>/` below.

75. **synthesis-content-quality v4.0** (companion skill). `synthesis-skills/skills/synthesis-content-quality/SKILL.md`. **V.** v2.0 depends on v4.0 for the slop-vs-fact distinction, A1 per-family fingerprinting catalog, and ESL safe-harbor methodology. [SKILL.md `depends_on`, C1-TOOLHALL, C1-TRANS, per-family signatures]

76. **content-quality v4.0 bibliography.** `synthesis-skills/skills/synthesis-content-quality/references/bibliography.md`. **V.** Shared-theory source-of-truth for entries this bibliography does not re-cite in full (Pinker, Lakoff, Pennycook, Frankfurt, Hicks-Humphries-Slater, Bender et al., Weidinger et al.).

77. **synthesis-writing-pitfalls.** `synthesis-skills/skills/synthesis-writing-pitfalls/SKILL.md`. **V.** Human-source error patterns complementary to AI-source patterns. [SKILL.md "Related skills," C1-NESTED]

78. **Unified Bucket C.** `<bucket>/unified-03-bucket-c-fact-checking.md`. **V.** Primary input that fed v2.0. [C1, C2, per-family signatures]

79. **Unified Bucket A: content-quality v4.0 catalog.** `<bucket>/unified-01-bucket-a-content-quality-catalog.md`. **V.** Feeds shared per-family fingerprinting. [C1-TOOLHALL]

80. **Unified Bucket B: cross-cutting layer.** `<bucket>/unified-02-bucket-b-cross-cutting-layer.md`. **V.** Feeds combined-signal methodology. [SKILL.md sections 1 and 2, C1-LAUNDER graph independence]

81. **Unified Bucket D: writing-pitfalls cross-references.** `<bucket>/unified-04-bucket-d-writing-pitfalls.md`. **V.** [synthesis-writing-pitfalls cross-reference]

82. **Upgrade plan.** `<bucket>/upgrade-plan.md`. **V.** Editorial recipe for v2.0; defines section structure and references/ layout.

---

## Verification status summary

| Status | Count |
|--------|-------|
| V (verified at expansion) | 9 |
| W (web-verified methodology/organization page) | 15 |
| C (cited only, unverified at expansion) | 58 |
| U (unreachable) | 0 |
| **Total** | **82** |

**Honest read:** 71 percent of entries arrive via the unified-bucket pipeline without independent fetching. Convergence across contributors raises the prior for each C-labeled entry, but a maintenance pass should upgrade C-to-V where feasible. W-labeled methodology pages were sanity-checked for existence and broad framing but not deep-read.

**Verification-flagged entries** (first-priority follow-up): #2 Rao Wong Callison-Burch 2026, #3 Topaz Lancet 2026, #4 Retrieval Collapse, #10 Magesh Stanford RegLab, #15 RIKER, #54 Mostafavi sanction, #55 Goldberg Segalla sanction, #56 Damien Charlotin database.

---

## Maintenance notes

When upgrading C to V or W: update the label inline, add the canonical URL or DOI, record any correction inline ("with correction"). If an entry is unreachable, label U and note what the search yielded; do not delete. Recompute the summary table. The compounding-archive principle applies: entries are relabeled, not deleted.

Cutoff for v2.0 entries: 2026-05-18. Post-cutoff additions go under a new "6. Post-v2.0 additions" section with entry date, maintainer initials, and the same verification protocol.
