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Use an evidence trail, not a detector. Save the answer and your original research, split the answer into verifiable claims, compare distinctive wording and paraphrased substance, and open every citation to test what it actually supports. This process can document overlap, missing attribution, or a citation that does not support a claim.
It cannot, by itself, prove which document an AI system accessed, what appeared in its training data, or how the system produced the text. Keep those questions separate: checking the output is an editorial and source-verification exercise; reconstructing model production history requires evidence that the available guidance does not provide.
What you can—and cannot—establish
Start by defining the finding you are trying to make. A careful review can answer three different questions, each with a different standard of evidence.
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|---|---|---|
| Does the answer overlap with my research? | Matching words, distinctive phrases, close paraphrases, matching facts, figures, sequence of ideas, or quotations; the exact locations in both texts. | A universal percentage threshold for “copying,” or proof that the model accessed your particular file. |
| Does the answer attribute and support its claims? | Whether a citation exists, identifies the claimed source, and actually supports the attached statement; whether quotations are accurate and attributed. | That a real citation makes the entire answer reliable, or that an unsupported claim was generated from your research. |
| How did the model produce the answer? | Usually, nothing in the final text alone can establish this production history. | The model’s training source, browsing path, hidden prompt, or internal process. |
The House of Commons Library recommends checking each factual claim against independent sources and warns that surface indicators of AI writing are not definitive. Its practical advice is succinct: “The best guard against hallucinations from AI is to check everything generated carefully, ideally with an expert.”
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Preserve the answer and your source material first
Do not begin by editing the output. Preserve what you received so another reviewer can reproduce your comparison.
- Save the complete AI answer. Keep the text, tables, footnotes, links, formatting that affects meaning, and the date and time received. Export a read-only copy if the service may change or delete the conversation.
- Save the research version used for comparison. Record the document title, author, publication date, version or revision date, and where the relevant passage appears. If your research changed over time, retain the version that was available when the answer was generated.
- Preserve citations and links exactly as shown. A later edit can hide a fabricated, redirected, or misapplied citation.
- Keep the prompt and surrounding conversation when policy and privacy allow. The prompt can show whether you supplied the research, requested a summary, or asked for independent work. Remove personal, confidential, or regulated information before sharing the record.
- Log human review. For publication or scientific work, note who checked claims, quotations, attribution, and references, and when.
APA Journals guidance encourages authors and editors to read original sources and preserve prompts or outputs where appropriate. Centers for Disease Control and Prevention guidance similarly emphasizes documenting tool use and having humans confirm attribution for quoted material. Those are examples of policy guidance; your journal, employer, school, or funder may set different requirements.
Break the answer into checkable claims
Read the answer sentence by sentence and mark anything that could be tested. A single sentence may contain several claims and should be split accordingly.
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- Numbers: dates, percentages, prices, measurements, sample sizes, and limits.
- Quotations: text in quotation marks or wording presented as someone else’s words.
- Interpretations: explanations of what evidence means, why a result matters, or how two sources relate.
- References: footnotes, inline links, named reports, papers, laws, standards, or webpages.
- Uncertainty and scope: words such as “always,” “proves,” “the study found,” geographic limits, edition numbers, and dates.
Give each claim an identifier in your notes. For example, “C-04: the report says the error rate fell after the change” is easier to verify than a paragraph highlighted as one block. The Commons Library’s workflow starts with this claim-level approach because a polished paragraph can mix accurate details with unsupported assertions.
Compare both wording and substance
Look for distinctive language
Search your original research for unusual strings of words: a memorable metaphor, an uncommon adjective-and-noun combination, a sequence of technical terms, or a sentence with an idiosyncratic structure. Record the exact match and its location. Short common phrases are weak evidence; a long, distinctive sequence is more informative.
Do not silently normalize the texts before recording them. Keep capitalization, punctuation, spelling, and quotation marks in your evidence copy, then make a separate copy with formatting removed if that helps you search.
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Check close paraphrases
An answer can preserve the idea while changing every sentence. Compare the entities, relationships, order of events, qualifiers, examples, and unusual grouping of points. A paraphrase is materially close when it carries the same specific information and structure—not merely when it discusses the same broad topic.
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| Comparison axis | Questions to ask |
|---|---|
| Exact wording | Are distinctive words or a continuous passage reproduced? Is it presented as a quotation? |
| Paraphrase | Are the same uncommon facts, examples, sequence, and qualifiers retained with only the wording changed? |
| Factual correspondence | Do names, dates, figures, and relationships match, including details that are not obvious from general knowledge? |
| Attribution | Does the answer identify your work or the underlying source where a reader would expect credit? |
| Context | Did the answer preserve limitations, uncertainty, population, geography, edition, or date? |
There is no source-backed universal similarity score that turns a match into proof of copying. Treat a comparison as a documented set of observations. Explain what matches, where it matches, and what alternative explanations remain.
Open every citation and test the attached claim
A citation is a lead, not evidence by itself. Open the cited page or document and perform four checks for each claim.
- Existence: Does the cited source resolve to a real document, from the stated publisher or author?
- Identity: Is it the source named in the answer, rather than a similarly titled page, search result, or unrelated document?
- Support: Does the source state or reasonably support the particular sentence next to the citation? Check the relevant page, table, footnote, methods section, or data definition.
- Scope: Does the source support the answer’s population, date, geography, edition, and level of certainty?
OpenAI’s “Does ChatGPT tell the truth?” guidance warns that systems can produce fabricated citations and recommends visiting source pages directly. A genuine source can still be misapplied: a report about one year may not support a claim about another, and a source that describes an association may not support a claim of causation.
Check quotations separately
Find the quotation in the original source, verify every word, and confirm that the speaker, date, and context are correct. If the answer gives no source for quoted material, record the quotation as unattributed rather than assuming it came from your research.
Check references that look plausible
Compare the title, author, publication, and date with the source itself. A plausible-looking journal name or URL is not confirmation. If a reference cannot be located, label it “unverified” in your log; do not replace it with a source that merely supports a similar point.
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Test whether the information is current and independently supported
Authority and currentness are different checks. A reputable source may be outdated, superseded, withdrawn, or limited to a context that no longer applies.
- Record the source’s publication and update dates.
- Check for later editions, corrections, retractions, amendments, or changed guidance.
- Find an independent authoritative source for contested, consequential, or surprising claims.
- Compare definitions and measurement methods before treating two numbers as conflicting.
- Preserve the source version you checked, because webpages and online documents can change.
Independent confirmation strengthens a finding about the claim’s reliability. It does not reveal whether an AI system copied your document. Keep source verification and production-history questions in separate columns in your notes.
Keep an evidence log another reviewer can audit
A compact log prevents conclusions from outrunning the evidence.
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|---|---|---|---|---|---|
| C-01 | Exact sentence or a short identifying excerpt | Document, section, page or paragraph | Exact wording, close paraphrase, unsupported, or no match | Accurate, missing, or misleading | Independent source, date check, or reviewer |
| C-02 | Claim and citation as received | Source page or table | Supported, partly supported, or not supported | Correct source and context? | Correction or escalation |
Attach screenshots or archived copies when permitted. Quote only as much text as needed to identify the match, and protect copyrighted, confidential, personal, or unpublished research.
Use precise language for your finding
Report what the record demonstrates, not a theory about hidden model behavior. Suitable descriptions include:
- “The answer reproduces a distinctive 18-word passage from section 3 of the manuscript without quotation marks or attribution.”
- “Claims C-02 and C-03 closely paraphrase the same sequence of examples and retain the manuscript’s qualification about the sample.”
- “The cited report exists, but its table covers 2022; it does not support the answer’s statement about 2025.”
- “The quotation could not be located in the cited source and remains unverified.”
- “The evidence documents textual overlap and missing attribution. It does not establish how the system obtained the material.”
Avoid declaring “the model stole my research” on the basis of a match alone. The same wording might have come from a public source, your prompt, a shared reference, or independent reproduction of standard language. Those possibilities may affect an institutional or legal decision, but they require evidence beyond the output comparison.
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Why asking the AI or running a detector is not proof
The model’s answer about its own authorship
OpenAI’s “Can I ask ChatGPT if it wrote something?” guidance says ChatGPT has no reliable knowledge of whether it generated a particular piece of writing and may invent an answer when asked. A confident “yes” or “no” is therefore not an authorship test. You may record that you asked, but treat the response as an unverified statement, not evidence.
Text classifiers and style signals
Classifiers that label text as AI-generated can produce false positives and false negatives, especially after editing, translation, or mixing human and machine writing. The House of Commons Library advises assessing evidence and source verifiability rather than relying on superficial style clues. A style label cannot show that your research was copied, identify the source, or establish missing attribution.
Provenance signals
OpenAI describes provenance tools as checking supported signals associated with OpenAI content. A detected signal may provide information about supported content origin, but it does not establish accuracy, legal ownership, authorship, or how much a model contributed. A missing signal is not proof that content was not AI-generated: signals may be unavailable, unsupported, removed, or degraded. These tools are designed for supported OpenAI signals, not as universal detectors for every AI system.
Watermarking limitations
OpenAI notes that short passages and code may not contain enough wording choices for reliable detection. Exact or highly factual wording, including text reproduced from a user-provided source, can also be harder to detect. Those limitations make a watermark result one contextual signal at most, never a substitute for checking the underlying sources.
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The answer summarizes research you supplied in the prompt
If you pasted or uploaded the material, the output may be a transformation of user-provided text rather than evidence that the system retrieved your unpublished work independently. Preserve the prompt, identify which passages were supplied, and assess whether the answer followed your requested attribution. Do not infer a training-data explanation from the match.
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Definitions, legal names, formulae, product specifications, and required terminology may match many sources. Weigh the distinctiveness of the expression and the combination of details. Attribute the underlying source where appropriate, but do not call unavoidable wording proof of copying.
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The answer translates or heavily edits the passage
Compare meaning, order, examples, and omissions in the original language as well as the translated text. Note who performed the translation and which version was reviewed. A translation can preserve a close paraphrase without preserving exact strings.
The answer contains code, equations, or very short text
Record functional and structural similarity, comments, variable names, unusual errors, and the source location. Text-based provenance methods may be especially limited for code and short passages, so source and attribution checks carry more weight.
A repeatable review checklist
- Save the answer, date, prompt where permitted, citations, and the relevant research version.
- List every factual, numerical, quoted, interpretive, and reference claim.
- Search for distinctive exact wording and record locations.
- Compare paraphrased substance, sequence, qualifiers, and omissions.
- Open every citation and verify existence, identity, support, and scope.
- Check dates, revisions, corrections, and independent confirmation.
- Mark attribution as present and accurate, incomplete, missing, or misleading.
- Record evidence and uncertainty in an auditable log.
- Use detectors, provenance signals, or a model’s self-report only as limited context, never as proof.
- State the narrow finding: overlap, unsupported attribution, or unsupported citation—not an unproven production history.
Match your documentation to the governing policy
Publication and research rules vary. Some journals require disclosure of generative-AI assistance; some institutions require prompt retention, human verification, or restrictions on confidential material. CDC scientific-work guidance calls for appropriate disclosure and human confirmation of attribution for quoted material. APA Journals’ policy guidance, updated in August 2025, gives its authors and editors additional instructions, including reading original sources and preserving relevant records. Consult the policy that governs your work before submitting or accusing someone of misconduct.
If the result may affect employment, grades, publication, funding, or a legal dispute, have a qualified human reviewer examine the original sources and your evidence log. Your strongest case is a transparent record of what matched, what was unsupported, what attribution was missing, and what remains unknowable.
Conclusion: make the narrowest defensible claim
The reliable way to check whether an AI-generated answer may have copied your research is to compare the output with the original at claim level, verify every citation against the source, and preserve a dated evidence trail. Report exact matches, close paraphrases, unsupported claims, and attribution failures with their locations and qualifications. Do not treat a detector, a provenance signal, or the model’s own answer as proof of copying or of the model’s internal process. The result is evidence about overlap and source quality—enough to guide correction, attribution, and policy review, but not a universal verdict about how the text was produced.
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