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

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
  3. Uribe S, Maldupa I. Estimating the use of ChatGPT in dental research publications. Journal of Dentistry 2024;149:105275 View
  4. Oermann M. You Cannot Search the Literature Using Artificial Intelligence, and This Is Why. Nursing Education Perspectives 2024;45(6):337 View
  5. Sun S, Huynh K, Cortes G, Hill R, Tran J, Yeh L, Ngo A, Houshyar R, Yaghmai V, Tran M, Moy L, Wolfe S. Testing the Ability and Limitations of ChatGPT to Generate Differential Diagnoses from Transcribed Radiologic Findings. Radiology 2024;313(1) View
  6. Kayabaşı M, Köksaldı S, Durmaz Engin C. Evaluating the reliability of the responses of large language models to keratoconus-related questions. Clinical and Experimental Optometry 2024:1 View