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AI-text detectors analyze statistical and linguistic patterns to estimate whether writing resembles AI-generated text. Understand the methods behind these tools, what their scores represent, and why detecting AI authorship remains uncertain.
Read Guide →Even academic text written entirely by a human can be flagged as AI-generated. Learn why legitimate research writing may trigger detection tools and how researchers can document and explain their authorship.
Read Guide →AI systems can perform tasks resembling scholarly contributions, but do they satisfy the requirements for academic authorship? Examine the four ICMJE criteria individually and understand why producing research content is not equivalent to qualifying as an author.
Read Guide →When AI generates most of a research manuscript, authorship does not automatically belong to the researcher who submitted it. Learn how scholarly contribution, human accountability, publisher policies, and disclosure requirements determine legitimate authorship.
Read Guide →Extensive AI assistance does not reduce a researcher's responsibility for the accuracy and integrity of a manuscript. Learn how authorship accountability applies when AI contributes to writing, analysis, interpretation, and other substantive research activities.
Read Guide →AI writing assistance may need to be reported in a research paper's acknowledgments, but the correct location depends on the journal and the nature of the assistance. Learn what to disclose, how specific the statement should be, and when AI use belongs in the methods section instead.
Read Guide →AI assistance may belong in the methods section, acknowledgments, or a designated disclosure statement, depending on how the tool was used. Learn why methodological AI use requires different reporting from writing assistance and how to follow journal-specific requirements.
Read Guide →Human authors remain responsible for AI-generated statements they incorporate into research manuscripts, but responsibility does not mean every error constitutes misconduct. Learn how accountability applies to citations, methods, findings, interpretations, and corrections.
Read Guide →Human accountability in AI-assisted authorship means retaining responsibility for scholarly decisions, evidence, interpretations, and published claims. Understand how accountability differs from merely reviewing AI outputs and what researchers must be able to explain and defend.
Read Guide →Researchers should disclose AI use when required by applicable policies, particularly when it materially contributes to manuscript content or research methods. Learn how disclosure obligations differ across writing, analysis, editing, and other activities, and when reporting should occur.
Read Guide →AI disclosure requirements depend on what the technology contributed to the research and the policies governing the work. Learn which AI-assisted activities commonly require reporting, which may be exempt, and how to distinguish manuscript preparation from methodological use.
Read Guide →AI-assisted grammar correction does not always require disclosure, but publisher policies differ. Learn when proofreading may be exempt, how substantive rewriting changes the obligation, and why the actual edits matter more than the name of the tool.
Read Guide →AI-assisted translation may require disclosure depending on the journal's policy and whether it affects manuscript preparation or research methods. Learn how to distinguish language translation from methodological translation, verify meaning, and report consequential AI assistance accurately.
Read Guide →Brainstorming with generative AI does not automatically require disclosure under every research policy. Learn when exploratory suggestions become substantive intellectual or methodological contributions, how publisher requirements apply, and why adopting an AI-generated idea differs from merely considering one.
Read Guide →AI-assisted literature searching may require disclosure when it materially affects how research evidence is identified, screened, or selected. Learn why exploratory searching differs from systematic evidence retrieval and how to report AI tools, search procedures, verification, and limitations.
Read Guide →AI-assisted research data coding may require disclosure because automated classifications can influence the findings. Learn when AI coding becomes a methodological contribution, what verification is necessary, and how to report the tool, coding framework, human oversight, and limitations.
Read Guide →AI-assisted statistical analysis generally warrants methodological disclosure when it materially influences analytical procedures or reported findings. Learn how to distinguish statistical software from generative AI assistance, verify AI-generated analyses, and report the tool's role without overstating its reliability.
Read Guide →AI-generated research code may require disclosure when it materially contributes to data processing, analysis, simulation, or published findings. Learn how to distinguish routine programming assistance from consequential AI-generated code, verify its correctness, and document its role in reproducible research.
Read Guide →AI-assisted qualitative analysis may require disclosure when it contributes to coding, theme development, or interpretation. Learn how to report AI involvement without misrepresenting methodological decisions, researcher reflexivity, or the credibility of qualitative findings.
Read Guide →AI-generated artwork and imagery may require disclosure or be prohibited under publisher policies, particularly when images represent research evidence. Learn how to distinguish illustrative artwork from scientific data, understand journal restrictions, and report permitted AI-generated visuals accurately.
Read Guide →AI use may need to be reported in the acknowledgments, methods section, a dedicated declaration, or multiple submission locations. Learn how to select the correct placement according to the tool's role, journal requirements, and the information readers need to evaluate the research.
Read Guide →Researchers do not universally need to publish every prompt used with AI, but prompts may be essential when they shape research procedures or findings. Learn when prompt disclosure supports reproducibility, how to document consequential instructions, and how to balance transparency with confidentiality and data protection.
Read Guide →Researchers should consider keeping records of consequential AI assistance, particularly when it influences research methods, evidence, analysis, or findings. Learn what documentation can establish, which interactions warrant preservation, and how AI-use records support transparency without requiring researchers to archive every conversation.
Read Guide →Researchers should consider preserving AI prompts that materially influence research procedures, analyses, or findings. Learn which prompts are worth saving, why prompts alone cannot guarantee reproducibility, and how to maintain useful records without exposing confidential research information.
Read Guide →Researchers should consider preserving AI-generated responses that materially influence research methods, analysis, or findings. Learn why prompts alone may be insufficient, which outputs warrant retention, and how to maintain accurate, secure, and useful records of AI assistance.
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