How to check citations in AI medical answers
A list of references gives you places to investigate an AI answer. To assess its evidence, check whether the references identify the intended sources, whether those sources support the attached claims, and how much of the answer has been checked. These are separate questions.
Researchers have formalized this distinction. The Attributable to Identified Sources framework evaluates whether generated statements can be supported by an identified source and provides guidelines for human annotation. It treats attribution as something to assess, rather than something established by displaying a reference. 1
What citation scores actually measure
A report should define its metric before presenting a score. The following definitions illustrate why seemingly similar citation claims can describe different results.
Citation presence.: Does the answer include a reference? This leaves open whether the reference identifies a real, relevant source.
Source identity.: Can the reference be matched to the intended document? This leaves open whether the document supports the claim.
Supported reference share.: What fraction of evaluated distinct references support their assigned claims? Claims without citations and the treatment of unresolved references remain separate questions.
At least one supported reference per answer.: Does an answer contain any verified supporting citation? This does not establish whether the rest of that answer has evidence.
Complete statement support.: Does every evaluated factual statement have supporting evidence? You still need to consider whether the statement inventory omitted anything and whether the evidence is clinically sufficient.
These distinctions also appear in medical citation research. SourceCheckup separately measures working source URLs, support for individual statements, and support for every statement in a response. Its method checks statements against the sources supplied with the answer; that is different from checking only the citation attached to a particular sentence. Comparisons need to say which relationship was assessed. 2
For example, an answer can have one well-supported sentence while leaving its other claims unsupported. It meets the “at least one” definition but fails the “every statement” definition. This follows from the definitions; it is not an estimate of how frequently either situation occurs.
A practical way to inspect an answer
Identify the claim. Mark the statement the citation is meant to support, including qualifications such as the population, timing or strength of the conclusion.
Match the source. Check the title, authors and publication details against the reference. A working link alone does not establish that it points to the intended document.
Read the relevant evidence. Compare the claim with the source passage. If you only have the abstract, record that limit. Unavailable or inconclusive evidence should stay distinguishable from evidence that contradicts the claim.
Check what was left out. Look for other factual claims without supporting citations. Several references attached to one statement do not establish support for the rest of the answer.
Read the denominator. When reviewing a study, ask whether its score counts references, statements or whole answers, and how it handles duplicates, inaccessible sources and answers without citations.
Citation assessment is also distinct from broader answer evaluation. The ALCE benchmark evaluates fluency, correctness and citation quality separately. A report that measures only one of these dimensions should keep its conclusion within that scope. 3
For readers comparing AI tools, the useful question is whether the publisher explains what was verified and provides evidence you can inspect. Reference volume alone leaves the support question unanswered. Citation checks also do not establish clinical effectiveness.
Sources
Evidence used in this article
- 1Measuring Attribution in Natural Language Generation Models
Rashkin and colleagues · Computational Linguistics · 2023
- 2An automated framework for assessing how well LLMs cite relevant medical references
Wu and colleagues · Nature Communications · 2025
- 3Enabling Large Language Models to Generate Text with Citations
Gao and colleagues · ALCE · 2023
AI-assisted explainer from ModernDoc, a developer of medical AI products. This article describes published evaluation methods and reports no new experiment or product comparison.