Comparisons of Quality, Correctness, and Similarity Between ChatGPT-Generated and Human-Written Abstracts for Basic Research: Cross-Sectional Study

• Published in: Journal of medical Internet research Vol. 25; no. 1; p. e51229
• Main Authors: Cheng, Shu-Li, Tsai, Shih-Jen, Bai, Ya-Mei, Ko, Chih-Hung, Hsu, Chih-Wei, Yang, Fu-Chi, Tsai, Chia-Kuang, Tu, Yu-Kang, Yang, Szu-Nian, Tseng, Ping-Tao, Hsu, Tien-Wei, Liang, Chih-Sung, Su, Kuan-Pin
• Format: Journal Article
• Language: English
• Published: Canada Journal of Medical Internet Research 25.12.2023; Gunther Eysenbach MD MPH, Associate Professor; JMIR Publications
• Subjects: Accuracy; Artificial Intelligence; Biology; Chatbots; Computational linguistics; Cross-Sectional Studies; Genomes; Genomics; Humans; Language; Language processing; Likert scale; Multimedia; Natural language interfaces; Original Paper; Plagiarism; Psychiatry; Research Personnel; Variables; generation; scientific research; natural language processing; abstracts; plagiarism; language model; AI-generated scientific content; abstract; LLM; academic research; extraction; artificial intelligence; textual; generative; NLP; extract; ChatGPT; publication; text; language models; publications

ChatGPT may act as a research assistant to help organize the direction of thinking and summarize research findings. However, few studies have examined the quality, similarity (abstracts being similar to the original one), and accuracy of the abstracts generated by ChatGPT when researchers provide fu...