Introduction: GPT-3 is a large language model that uses artificial intelligence to generate textual responses to prompts and questions. GPT-3 technology has been used to create several interesting tools including the widely reported chatbot ChatGPT-3, which was released in November 2022. Inspired by the initial success of GPT-3, several organizations have started to build tools designed to assist with tasks associated with the systematic review research process. This project will analyze how successful these tools are in completing two specific tasks: searching for research articles and analyzing individual articles.
Methods/Description: This project consists of two parts. In part one, the research question from a previously published systematic review will be used to conduct a search in two GPT-3 based tools for relevant research articles. In part two, each GPT-3 tool will be used to analyze a single research article to determine if it is relevant to the research question.
Results/outcomes: For part one, the results will be based on how effective and efficient each tool is at finding relevant research articles. Results will be compared to the set of articles included in the original review as a measure of success. For part two, each tool will be used to pull evaluative information from the sample article. This information will be compared to a manual assessment completed by the author.
Discussion: This project will provide researchers with guidance on how to integrate GPT-3 based tools into their systematic review workflow. It will include a brief discussion of strengths and weaknesses and how they can impact potential results.
ChatGPT-3, artificial intelligence, systematic review methodology
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Atwood, Gary S., "Can GPT-3 Tools Accurately Find and Analyze Articles for Systematic Reviews? A (Very) Preliminary Assessment" (2023). University Libraries Faculty and Staff Publications. 97.