Exploring Elicit-AI Powered Literature Research Tool: Insights from a Topic on Digitalization in Insect Science
Exploring Elicit-AI Powered Literature Research Tool: Insights from a Topic on Digitalization in Insect Science
Nahdia Perveen
ABSTRACT
Elicit is a powerful research assistant tool based on language models like GPT-3, and uses semantic similarity to search articles relevant to a research question among multiple databases. This article evaluates the effectiveness of the Elicit-AI tool in facilitating literature research for the topic of “Digitization in Insect Science.” As digital technologies increasingly transform entomological research, the ability to efficiently navigate the growing body of scientific literature is crucial. Elicit-AI, an AI-powered literature research tool, promises to streamline the process of data collection, synthesis, and knowledge extraction. Through a case study focused on digitalization in insect science, I demonstrated how Elicit-AI aids researchers in identifying key trends, summarizing complex research, and uncovering emerging themes. By posing specific queries related to digital technologies in insect study, I assessed the tool’s accuracy, relevance, and utility. About 81% of the articles were most relevant to the given keywords, digitalization, and insect science; however, 12% of the articles were related to the latest area in the field of entomology. The results highlight Elicit-AI’s ability to quickly locate relevant studies, generate useful insights, and enhance the literature review process. However, challenges such as the need for more nuanced search parameters and refinement of results are also discussed. Ultimately, this study underscores the potential of AI-driven research tools like Elicit-AI to support efficient, high-quality literature reviews, offering new avenues for research in digitization across scientific disciplines.
Novelty Statement | The study highlights the efficiency of Elicit-AI in streamlining the literature review process by accurately retrieving and synthesizing relevant research on a specialized topic.
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