The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research

45 indexed citations
published 2024

Countries where authors are citing The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research

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Citations

This map shows the geographic impact of The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research more than expected).

Fields of papers citing The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research.

About The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research

This paper, published in 2024, received 45 indexed citations . Written by Liesbet Van Bulck and Charlotta Lindvall covering the research area of General Health Professions and Health. It is primarily cited by scholars working on Health Informatics (21 citations), Artificial Intelligence (18 citations) and Radiology, Nuclear Medicine and Imaging (10 citations). Published in JMIR Human Factors.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/10.2196/53559.

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