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Generative AI can suggest variables that may explain how a relationship operates or when its magnitude changes. Learn how to evaluate potential mediators and moderators using theory, causal assumptions, temporal ordering, and appropriate research designs.
Read Guide →Generative AI can propose plausible causal variables, but familiar concepts and convincing explanations do not establish causality. Learn why every suggested variable requires substantive justification before it enters a causal model, research hypothesis, or adjustment strategy.
Read Guide →AI can make a research question sound clearer while quietly changing what the study investigates. Learn how to detect construct substitution, causal language, scope changes, and other forms of meaning drift before accepting AI-generated revisions.
Read Guide →Generative AI can suggest research questions, variables, hypotheses, and methods, but it cannot assume responsibility for the decisions that define a study. Learn which intellectual judgments must remain with the researcher and how to use AI without surrendering control of the inquiry.
Read Guide →Generative AI can help researchers discover scientific papers, clarify search concepts, and explore unfamiliar research areas. Its usefulness depends on how it retrieves evidence, how results are verified, and whether the search process can be documented.
Read Guide →Asking generative AI to recommend research papers may help you discover useful studies, but it does not necessarily constitute a literature search. The difference lies in how publications are retrieved, selected, verified, and documented.
Read Guide →Generative AI can help identify recently published scientific research, particularly when connected to current scholarly retrieval sources. However, finding the most recent studies requires distinguishing publication dates from indexing dates, verifying source coverage, and accounting for delays in database updates.
Read Guide →Finding a real research paper is only the beginning. Before citing an AI-suggested publication, researchers must verify its bibliographic identity, examine what the study actually found, assess its relevance, and check whether the evidence supports the manuscript's claim.
Read Guide →A DOI can identify a genuine publication without confirming that the paper supports the claim attached to it. Learn the difference between DOI verification and evidence verification, and how to check whether a citation genuinely supports your argument.
Read Guide →A research paper can be genuine while the findings AI attributes to it are incorrect. Learn how generative AI misrepresents real studies, why DOI verification is insufficient, and how to check whether a source supports a particular claim.
Read Guide →Using AI with academic references does not have to mean risking fabricated citations or unsupported claims. Follow a practical workflow that separates literature discovery, source verification, evidence evaluation, reference management, and final manuscript checks.
Read Guide →Generative AI can help researchers navigate complex papers, clarify unfamiliar concepts, and organize their reading. Learn where it adds value, where it can mislead, and how to use it without surrendering scholarly judgment.
Read Guide →Generative AI can make difficult research papers easier to understand, but simplifying academic language can also distort important concepts. Learn how to request clearer explanations while preserving the study's original meaning.
Read Guide →Generative AI can produce useful summaries of research papers, but fluent writing does not guarantee factual accuracy. Learn how to distinguish faithful summaries from misleading ones and verify the details that matter most.
Read Guide →An AI summary can report a study's main finding correctly while omitting qualifications that change its meaning. Learn which details must survive summarization and how to detect misleading omissions.
Read Guide →Generative AI can identify research questions in academic papers, but it may confuse objectives, hypotheses, and findings or invent questions the authors never stated. Learn how to verify what a study was actually designed to investigate.
Read Guide →Generative AI can identify study designs from research papers, but methodological labels may be misleading. Learn how to verify a design using the procedures researchers actually followed.
Read Guide →AI can extract sample sizes and participant characteristics from research papers, but a study may report several different participant counts. Learn how to distinguish recruitment, enrollment, analysis, and attrition while verifying extracted information.
Read Guide →Generative AI can identify a study's primary outcome, but it may confuse the most prominent finding with the outcome researchers originally intended to measure. Learn how to verify outcome definitions, prespecification, and reporting.
Read Guide →Generative AI can identify statistical tests and models used in research papers, but it may confuse procedures, overlook analytical details, or infer methods that were never reported. Learn how to verify what researchers actually used.
Read Guide →Generative AI can help identify limitations in research papers, including restrictions acknowledged by the authors. However, it may invent weaknesses, overlook important concerns, or mistake legitimate methodological choices for flaws.
Read Guide →Generative AI can assist with critical appraisal by examining research methods, identifying possible bias, and questioning conclusions. Learn how to use established appraisal frameworks without treating AI-generated judgments as verified assessments.
Read Guide →Generative AI may identify methodological problems that research authors did not acknowledge, but it can also invent weaknesses or misapply methodological standards. Learn how to distinguish evidence-supported concerns from speculative criticism.
Read Guide →Generative AI can help researchers plan, organize, synthesize, and draft literature reviews, but fluent writing does not guarantee an accurate representation of the evidence. Learn which tasks AI can reasonably support, where errors arise, and how to retain control over the scholarly argument.
Read Guide →Generative AI can help identify relationships across research papers and draft an integrated synthesis, but combining findings requires more than summarizing individual studies. Learn how to preserve methodological differences, conflicting evidence, and source traceability.
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