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AI Output Verification Kit

Quick Reference Card + 27-point Hallucination Detection Checklist for verifying AI-generated content before publishing.

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Quick Reference Card

The 4-Phase Process

EXTRACT → VERIFY → SCORE → REPORT

EXTRACT

  • Break AI output into individual verifiable claims
  • Tag each claim by type: statistic, attribution, quote, or inference
  • Prioritize high-stakes claims for verification first

VERIFY

  • Check each claim against reliable, independent sources
  • Apply the source reliability hierarchy to weight evidence
  • Document verification status for every claim

SCORE

  • Assign a confidence score to the overall document
  • Map the score to confidence bands: HIGH, MODERATE, LOW, or INSUFFICIENT
  • Flag claims that cannot be verified and assess their risk

REPORT

  • Document findings, corrections, and unresolved claims
  • Note the risk level of any unverified content
  • Produce a publish, revise, or rewrite recommendation

Source Reliability Hierarchy

  1. 1Primary sources greater than
  2. 2Peer-reviewed greater than
  3. 3Institutional greater than
  4. 4Industry greater than
  5. 5AI-generated

Confidence Bands

HIGH(90%+)
MODERATE(70–89%)
LOW(50–69%)
INSUFFICIENT(<50%)

Hallucination Detection Checklist

27 systematic checks across 6 fabrication categories

1. Fabricated Sources

  • Cited paper or report does not exist in scholarly databasesCritical
  • Author name does not match any real publication recordCritical
  • Journal or publisher name is invented or misspelled to appear legitimateCritical
  • DOI or URL provided does not resolve to the claimed sourceCritical
  • Citation attributes a real paper to the wrong author or institutionHigh

2. Statistical Fabrication

  • Statistic cannot be found in the cited original sourceCritical
  • Number is close but not exact to the source (e.g., 32% vs 35%)High
  • Implausible precision without cited methodology (e.g., "exactly 47.3%")High
  • Sample size or study scope misrepresentedMedium
  • Statistic applied to wrong industry, region, or demographicHigh

3. Temporal Errors

  • Data from prior years presented as current without date qualificationHigh
  • Laws, regulations, or policies cited that have been supersededHigh
  • Product features, pricing, or leadership roles that have changedMedium
  • Anachronistic claims (events referenced before they occurred)Critical

4. Attribution Errors

  • Direct quote cannot be found in attributed person's published workHigh
  • Paraphrased content presented as a direct quotationHigh
  • Quote attributed to wrong person or organizationHigh
  • Title or role of quoted individual is incorrectMedium

5. Logical Fabrication

  • Correlation presented as causation without supporting evidenceHigh
  • Cherry-picked examples presented as established trendsHigh
  • Circular reasoning (conclusion used as premise)Critical
  • Missing counterpoints or contradictory evidence omittedMedium
  • Conclusion does not follow from the evidence presentedHigh

6. Confidence Miscalibration

  • Hedging language ("may", "suggests") removed to state speculation as factHigh
  • Uncertain claims presented with unwarranted certaintyHigh
  • Confidence level exceeds what sources actually supportHigh
  • Limitations and caveats from sources stripped from summaryMedium

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When you need more

This checklist tells you what to check. The Verification System shows you how to check systematically — with claim extraction worksheets, source verification matrices, confidence scoring, and report templates.

Methodology reviewed: August 2026. Next review: November 2026.

Version 1.0 — Based on AI Research Verification System methodology

License: Free for personal and professional use. Attribution appreciated.