scite awarded NIH SBIR Fast-Track grant

Grant will be used to develop a deep learning platform for evaluating the reliability of scientific claims by citation analysis.

scite
scite
Oct 7 · 2 min read

Brooklyn, NY– October 07, 2019– Scite, Inc., a Brooklyn-based startup focused on making research more reliable, has been awarded a Small Business Innovation Research (SBIR) Fast-Track grant by the National Institute on Drug Abuse (NIDA) of the National Institutes of Health (NIH) to conduct further research required for developing and commercializing a platform that identifies studies supporting or contradicting prior research. The award is issued in two phases with a Phase I limit of $225,000 and a Phase II limit of $1,500,000 with the second phase contingent upon meeting specific milestones.

The beta version of the platform is already publicly available at scite.ai and allows anyone to see how a scientific article has been cited, specifically whether it has been supported or contradicted.

Phase I of the research funded by this Fast-Track grant will focus on further development of scite’s machine learning classifier and on improving the extraction of citation statements from the scientific literature. Phase II will focus on research required to commercialize the technology.

Josh Nicholson, co-founder and CEO of scite says, “We’re absolutely thrilled to receive this grant and to be working with NIDA. The ability to extract citation statements from scientific articles and classify them automatically is exceedingly difficult and we’re excited to have the resources towards testing new techniques to improve the process.”

About scite

scite is a Brooklyn-based startup that allows anyone to see how a scientific report has been cited, specifically if it has been supported or contradicted. Using deep learning and a network of experts, scite has already classified over 420 million citation statements from 12 million scientific articles that support, contradict, or mention prior research and intends to do so for all scientific publications. scite is used by researchers from dozens of countries and has been funded in part by the National Science Foundation and the National Institutes of Health.

NIH Disclaimer

The research proposal described herein was supported by the National Institute on Drug Abuse of the National Institutes of Health under Award Number 1 R44 DA050155–01. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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scite combines natural language processing with a network of experts to evaluate the veracity of scientific work

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scite combines deep learning with a network of experts to evaluate the veracity of scientific work

scite

scite

scite combines natural language processing with a network of experts to evaluate the veracity of scientific work

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