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Artículo

The language model based on sensitive artificial intelligence – ChatGPT: Bibliometric analysis and possible uses in agriculture and livestock

Resumen

ChatGPT adds to the list of artificial intelligence-based systems designed to perform specific tasks and answer questions by interacting with users (Apple’s Siri, Amazon’s Alexa, Google’s Assistant and Bard, Microsoft’s Cortana, IBM’s Watson, Bixby from Samsung, among others). ChatGPT works using OpenAI’s GPT (Generative Pretrained Transformer) language model and is capable of learning from users’ preferences and behavior patterns to customize its response. ChatGPT has the potential to be applied in different fields, including education, journalism, scientific writing, communication, cell biology, and biotechnology, where there is already evidence. The aim of this work was to analyze the possible applications of ChatGPT in the agricultural and livestock industry. First, a scientometric analysis was performed with VosViewer and Bibliometrix (Bliblioshiny). 3 clusters were identified: (a) Main characteristics; (b) learning systems you use; and (c) applications. To the question: What are the main applications in which ChatGTP will revolutionize agriculture (or livestock) in the world? ChatGPT responded: (a) in the agricultural field: improvement of agricultural decision-making, optimization of agricultural production, detection and prevention of plant diseases, climate management, and supply chain management; and (b) in the livestock field: improvement of animal health and welfare, optimization of animal production, supply chain management, detection and prevention of zoonotic diseases, and climate management for animal production. ChatGPT does not scientifically support its answer, but from the analysis carried out, we find that there is enough scientific evidence to conclude, in this case, that its answers were correct. While ChatGPT does not necessarily scientifically substantiate its answers, users should. There is a lack of studies on the use of Artificial Intelligence and its relationship with ethics.
Zhao, Jinlong (57204615579); Zeng, Lingfeng (55635553800); Wei, Wanjia (59453408000); Liang, Guihong (57194134199); Yang, Weiyi (56047615500); Fu, Haoyang (56048255500); Zeng, Yuping (59422387300); Liu, Jun (55351349000); Zhao, Shuai (57205881934)
Knowledge Graph of Endoscopic Techniques Applied to the Treatment of Lumbar Disc Herniation: A Bibliometric Analysis
2024
10.1097/BSD.0000000000001648
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210777192&doi=10.1097%2fBSD.0000000000001648&partnerID=40&md5=6350efbc348cb2d2c3f6a29f0268e690
The Second Clinical College, Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, China; The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, China; The Research Team on Bone and Joint Degeneration and Injury, Guangdong Provincial Academy of Chinese Medical Sciences, China; Medical College of Acupuncture-Moxibustion and Rehabilitation, Guangzhou University of Chinese Medicine, China; Guangdong Second Chinese Medicine Hospital, Guangdong Province Engineering Technology, Research Institute of Traditional Chinese Medicine, Guangzhou, China
All Open Access; Green Open Access
Scopus
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