Evidence map›Paper›PMID 41833014›Full record

ArticleAccountability in research2026

Hallucinated citations produced by generative artificial intelligence may constitute research misconduct when citations function as data in scholarly papers.

David B Resnik, Mohammad Hosseini

Abstract read
In one paragraph

Article in Accountability in research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

David B ResnikNational Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA.
Mohammad HosseiniDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.ORCID 0000-0002-2385-985X

Funding

NUCATS CTSA UM1 at Northwestern UniversityUM1TR005121 · NCATS · NORTHWESTERN UNIVERSITY AT CHICAGO · PI Sara Becker, Richard D'Aquila · 2024 to 2026
$23.4M
NCATS NIH HHS UM1 TR005121
6 · The paper itself

Abstract

In this article, we discuss the growing problem of hallucinated citations produced by Generative Artificial Intelligence (GenAI) in scholarly research and writing. We argue that GenAI hallucinated citations might qualify as a provable instance of research misconduct under the U.S. federal regulations when a) the researcher uses a GenAI tool to produce hallucinated (i.e., nonexistent) citations for a research document; b) the citations function as data because they directly support research findings, as in, for example, review articles or bibliometric studies; and c) the researcher demonstrates indifference to the risk of fabrication of the data (i.e. citations) because they did not check the GenAI's output for veracity and accuracy. Other types of problematic citations such as bibliometrically incorrect citations, or contextually inaccurate citations, are indicative of poor scholarship and irresponsible behavior, but do not qualify as research misconduct. Recognizing that GenAI hallucinated citations could be regarded as research misconduct in certain cases will hopefully encourage researchers to take this problem more seriously than they do now. In partnership with scientific institutions, funders and professional societies, the scholarly community should work on establishing, promoting, and enforcing standards for responsible use of AI in research, including standards pertaining to citation practices.

Indexed as

Generative Artificial IntelligenceScientific MisconductHumansUnited Statesfabricationgenerative artificial intelligenceHallucinated citationspublication ethicsresearch misconduct

Identifiers

PMID41833014
PMCPMC13051339

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.