![]() Citation indices have facilitated the discovery and evaluation of scientific findings across all fields of research. The first citation index in science, created in 1960 by Eugene Garfield and the Institute for Scientific Information, aimed to “be a spur to many new scientific discoveries in the service of mankind” ( Garfield, 1959). Here we describe how scite works and how it can be used to further research and research evaluation.Ĭitations are a critical component of scientific publishing, linking research findings across time. ![]() Scite has been developed by analyzing over 25 million full-text scientific articles and currently has a database of more than 880 million classified citation statements. Scite shows how a citation was used by displaying the surrounding textual context from the citing paper and a classification from our deep learning model that indicates whether the statement provides supporting or contrasting evidence for a referenced work, or simply mentions it. To solve this problem, we have used machine learning, traditional document ingestion methods, and a network of researchers to develop a “smart citation index” called scite, which categorizes citations based on context. The use of citations in research evaluation without consideration of context can be problematic because a citation that presents contrasting evidence to a paper is treated the same as a citation that presents supporting evidence. ![]() ![]() Citation indices help measure the interconnections between scientific papers but fall short because they fail to communicate contextual information about a citation. Citation indices are tools used by the academic community for research and research evaluation that aggregate scientific literature output and measure impact by collating citation counts.
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