This paper is in the following e-collection/theme issue:

Generative Language Models Including ChatGPT (218) Chatbots and Conversational Agents (473) Scientometrics, Infometrics, and Altmetrics (84) Epublishing and Open Access (80) Artificial Intelligence (1214) Ontologies, Classifications, and Coding (226) Development and Evaluation of Research Methods, Instruments and Tools (439)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52935, first published .
Evaluation of Large Language Model Performance and Reliability for Citations and References in Scholarly Writing: Cross-Disciplinary Study

Evaluation of Large Language Model Performance and Reliability for Citations and References in Scholarly Writing: Cross-Disciplinary Study

Evaluation of Large Language Model Performance and Reliability for Citations and References in Scholarly Writing: Cross-Disciplinary Study

Authors of this article:

Joseph Mugaanyi1 Author Orcid Image ;   Liuying Cai2 Author Orcid Image ;   Sumei Cheng2 Author Orcid Image ;   Caide Lu1 Author Orcid Image ;   Jing Huang1 Author Orcid Image
Article Authors Cited by (2) Tweetations (9) Metrics

Journals

  1. Luo X, Chen F, Zhu D, Wang L, Wang Z, Liu H, Lyu M, Wang Y, Wang Q, Chen Y. Potential Roles of Large Language Models in the Production of Systematic Reviews and Meta-Analyses. Journal of Medical Internet Research 2024;26:e56780 View
  2. Norberg K, Almoubayyed H, De Ley L, Murphy A, Weldon K, Ritter S. Rewriting Content with GPT-4 to Support Emerging Readers in Adaptive Mathematics Software. International Journal of Artificial Intelligence in Education 2024 View