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What are Topic and Topic Cluster summaries and titles?
Last updated on June 16, 2025
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SciVal Topic summaries and titles are powered by generative AI (GenAI) and LLM technology. Titles and abstracts of publications in a Topic/Topic Cluster are processed to create summaries and titles designed to help users quickly gain an understanding of the research fields and questions being addressed within the Topic.

The summaries are pre-generated for all Topics and Topic Clusters, so the same version is always displayed to all users. All publications strongly linked to a Topic are used to generate the summaries and titles, so they do not change across different year range selections.
You can access the summaries by clicking "About this Topic/Topic Cluster" link in the Topic entity header, or "i" icon in the Topic listings.

Feedback is welcome and functionality to provide this is available at the bottom of each summary and will be used for improvement of them moving forward.
The summaries and titles are built using a combination of LLM technologies and prompt engineering developed by Elsevier and third-party providers, including the GPT (generative pre-trained transformer) developed by OpenAI for its ChatGPT tool. Our use of the OpenAI GPT is private, so there is no data exchange or use of the data to train ChatGPT
We uphold Elsevier Responsible AI Principlesopens in new tab/window, aiming to remove unfair bias, ensure accountability, and champion robust data governance.
Please note
While SciVal Topic and Topic Cluster GenAI summaries and titles leverage trusted Scopus content, it is still possible to produce misleading or inaccurate results. We recommend exercising your expertise and discretion before incorporating the summaries or titles into official documents like dissertations or manuscripts. It is essential to understand that SciVal summaries and titles are not designed to offer expert advice, for example legal, financial, or medical advice. Additionally, be aware that the summaries and titles may contain content perceived as biased or offensive.

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