Development of a Natural Language Processing algorithm for the topic and novelty identification of scientific articles

Currently the selection of peer reviewers is a secret process entirely controlled by journal editors. This introduces significant biases into the process that fosters an environment that contravenes every aspect of equity, diversity and inclusivity, inhibits novel ideas and suppresses creativity which is just bad for science as a whole. Furthermore, research is most often published behind paywalls, making taxpayer funded research inaccessible to the average Canadian. Peer Premier is leading the charge to democratize scientific dissemination. We are using Artificial Intelligence, specifically the field of Natural Language Processing to match appropriate reviewers to papers requiring peer review. This will remove biases, increase peer review transparency and increase the quality, novelty and diversity of science. Providing a professional, certified peer review in a transparent manner will negate the requirement of having to publish the paper behind paywalls and scientific authors will be free to post their professionally peer-reviewed paper making it free to all Canadians who funded their research.

Faculty Supervisor:

Zeny Feng;Lorna Deeth

Student:

Partner:

Peer Premier Inc.

Discipline:

Mathematics

Sector:

Professional, scientific and technical services

University:

University of Guelph

Program: