About Scite
Scite is a research intelligence platform that helps users evaluate the reliability of scientific claims by analyzing how published papers have been cited. Unlike standard citation counters, Scite categorizes each citation as supporting, contrasting, or simply mentioning the referenced work. This distinction gives researchers a clearer picture of whether a study's findings have been reinforced or challenged by subsequent literature, rather than treating all citations as equivalent endorsements. The platform's primary use cases include literature review, fact-checking scientific claims, and assessing the credibility of specific studies before relying on them. Researchers can search for a paper, author, or topic and receive a breakdown of how the work has been received across the broader literature. Scite also offers a Smart Citations feature that surfaces the actual sentences in which a paper is cited, providing direct context rather than requiring users to track down and read each citing paper manually. An AI assistant layer allows users to ask research questions and receive answers grounded in published literature, with citations attached so claims can be traced back to their sources. Scite is aimed primarily at academic researchers, scientists, students, and professionals in evidence-heavy fields such as medicine, life sciences, and social sciences. It is also useful for journalists, policy analysts, and anyone who needs to verify whether a scientific claim has held up under scrutiny. The platform operates on a subscription model, with individual plans available for regular users and institutional licenses offered for universities and research organizations. A limited free tier allows basic searching and access to some citation data, while full access to Smart Citations, the AI assistant, and deeper analytics requires a paid subscription. Scite indexes hundreds of millions of citation statements drawn from a large corpus of scientific literature, making it a substantive tool for anyone conducting serious evidence evaluation.
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