Purpose: The integration of generative artificial intelligence (GAI) into scientific research and academic writing has generated considerable controversy. Currently, standards for using GAI in academic medicine remain undefined. This study aims to conduct a comprehensive analysis of the guidance provided for authors regarding the use of GAI in ophthalmology scientific journals.
Design: Cross-sectional bibliometric analysis.
Participants: A total of 140 ophthalmology journals listed in the Scimago Journal & Country Rankings, regardless of language or origin.
Methods: We systematically searched and screened the 140 ophthalmology journals' websites on October 19 to 20, 2024, and conducted updates on November 19 to 20, 2024.
Main Outcome Measures: The content of GAI guidelines from the websites of the 140 ophthalmology journals.
Results: Of the 140 journals, 96 (69%) provide explicit guidelines for authors regarding the use of GAI. Among these, nearly all journals agree on three key points: 1) 94 journals (98%) have established specific guidelines prohibiting GAI from being listed as an author. 2) 94 journals (98%) emphasize that human authors are responsible for the outputs generated by GAI tools. 3) All 96 journals require authors to disclose any use of GAI. Additionally, 20 journals (21%) specify that their guidelines pertain solely to the writing process with GAI. Furthermore, 92 journals (66%) have developed guidelines concerning GAI-generated images, with 63 journals (68%) permitting their use and 29 (32%) prohibiting them. Among those that prohibit GAI images, 27 journals (93%) allow their use under specific conditions.
Conclusions: Although there is considerable ethical consensus among ophthalmology journals regarding the use of GAI, notable variations exist in terms of permissible use and disclosure practices. Establishing standardized guidelines is essential to safeguard the originality and integrity of scientific research. Researchers must uphold high standards of academic ethics and integrity when utilizing GAI.
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http://dx.doi.org/10.1016/j.ajo.2024.12.021 | DOI Listing |
EMBO J
January 2025
College of Life Sciences, Nanjing Agricultural University, 210095, Nanjing, China.
Chloride (Cl) ions cause major damage to crops in saline soils. Understanding the key factors that influence Cl uptake and translocation will aid the breeding of more salt-tolerant crops. Here, using genome-wide association study and transcriptomic analysis, we identified a NITRATE TRANSPORTER 1 (NRT1)/PEPTIDE TRANSPORTER family (NPF) protein, GmNPF7.
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December 2024
Department of Obstetrics and Gynaecology, The First Hospital of Jilin University, Changchun 130021, China. Electronic address:
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Anal Chem
January 2025
College of Chemistry and Pharmaceutical Sciences, Qingdao Agricultural University, Qingdao 266109, P. R. China.
Neonicotinoid insecticides have been widely applied in modern agriculture to improve crop productivity, but their residues have adverse impacts on the environment and human health. Hence, to address these issues, a portable self-powered/colorimetric dual-mode sensing platform was developed for the simple, rapid, precise, and sensitive on-site detection of acetamiprid (ATM) residues in vegetables. In this case, a multifunctional bioconjugate with specific recognition capability, excellent enzyme-like activity, and loading capacity is the key to the sensing design.
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December 2024
Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil.
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