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      PreprintMatch: A tool for preprint to publication detection shows global inequities in scientific publication

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      PLOS ONE
      Public Library of Science

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          Abstract

          Preprints, versions of scientific manuscripts that precede peer review, are growing in popularity. They offer an opportunity to democratize and accelerate research, as they have no publication costs or a lengthy peer review process. Preprints are often later published in peer-reviewed venues, but these publications and the original preprints are frequently not linked in any way. To this end, we developed a tool, PreprintMatch, to find matches between preprints and their corresponding published papers, if they exist. This tool outperforms existing techniques to match preprints and papers, both on matching performance and speed. PreprintMatch was applied to search for matches between preprints (from bioRxiv and medRxiv), and PubMed. The preliminary nature of preprints offers a unique perspective into scientific projects at a relatively early stage, and with better matching between preprint and paper, we explored questions related to research inequity. We found that preprints from low income countries are published as peer-reviewed papers at a lower rate than high income countries (39.6% and 61.1%, respectively), and our data is consistent with previous work that cite a lack of resources, lack of stability, and policy choices to explain this discrepancy. Preprints from low income countries were also found to be published quicker (178 vs 203 days) and with less title, abstract, and author similarity to the published version compared to high income countries. Low income countries add more authors from the preprint to the published version than high income countries (0.42 authors vs 0.32, respectively), a practice that is significantly more frequent in China compared to similar countries. Finally, we find that some publishers publish work with authors from lower income countries more frequently than others.

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          Open access: The true cost of science publishing.

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              The evolving role of preprints in the dissemination of COVID-19 research and their impact on the science communication landscape

              The world continues to face a life-threatening viral pandemic. The virus underlying the Coronavirus Disease 2019 (COVID-19), Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has caused over 98 million confirmed cases and 2.2 million deaths since January 2020. Although the most recent respiratory viral pandemic swept the globe only a decade ago, the way science operates and responds to current events has experienced a cultural shift in the interim. The scientific community has responded rapidly to the COVID-19 pandemic, releasing over 125,000 COVID-19–related scientific articles within 10 months of the first confirmed case, of which more than 30,000 were hosted by preprint servers. We focused our analysis on bioRxiv and medRxiv, 2 growing preprint servers for biomedical research, investigating the attributes of COVID-19 preprints, their access and usage rates, as well as characteristics of their propagation on online platforms. Our data provide evidence for increased scientific and public engagement with preprints related to COVID-19 (COVID-19 preprints are accessed more, cited more, and shared more on various online platforms than non-COVID-19 preprints), as well as changes in the use of preprints by journalists and policymakers. We also find evidence for changes in preprinting and publishing behaviour: COVID-19 preprints are shorter and reviewed faster. Our results highlight the unprecedented role of preprints and preprint servers in the dissemination of COVID-19 science and the impact of the pandemic on the scientific communication landscape. An analysis of bioRxiv and medRxiv during the first 10 months of the COVID-19 pandemic reveals that the pandemic has resulted in a cultural shift in the use of preprints for disseminating pandemic-related science.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2023
                8 March 2023
                : 18
                : 3
                : e0281659
                Affiliations
                [1 ] Department of Computer Science and Engineering, UC San Diego, La Jolla, CA, United States of America
                [2 ] Department of Neuroscience, UC San Diego, La Jolla, CA, United States of America
                The University of Arizona, UNITED STATES
                Author notes

                Competing Interests: AB is a founder, member of the board of directors and the CEO of SciCrunch Inc, a company that works with publishers to improve the representation of research resources in scientific literature. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Author information
                https://orcid.org/0000-0002-5388-9451
                https://orcid.org/0000-0002-5497-0243
                Article
                PONE-D-22-23440
                10.1371/journal.pone.0281659
                9994746
                36888577
                55a5869a-a95e-4b48-9dfe-e42d114b52ba
                © 2023 Eckmann, Bandrowski

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 22 August 2022
                : 30 January 2023
                Page count
                Figures: 6, Tables: 4, Pages: 20
                Funding
                Funded by: Chan Zuckerberg Initiative DA
                Award ID: 2022-250218
                Funded by: NSF’s Extreme Science and Engineering Discovery Environment
                Award ID: 1341698
                Funded by: NSF’s REHS program at the San Diego Supercomputer Center
                This work was supported in part by the NSF’s Extreme Science and Engineering Discovery Environment award number 1341698 ( https://www.xsede.org/), and by the NSF’s REHS program at the San Diego Supercomputer Center ( https://education.sdsc.edu/studenttech/rehs-home/). This project has been made possible in part by grant 2022-250218 from the Chan Zuckerberg Initiative DAF, an advised fund of the Silicon Valley Community Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Research and Analysis Methods
                Research Assessment
                Peer Review
                Social Sciences
                Economics
                Economic Geography
                Low Income Countries
                Earth Sciences
                Geography
                Economic Geography
                Low Income Countries
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Psychology
                Language
                Biology and Life Sciences
                Psychology
                Cognitive Psychology
                Language
                Social Sciences
                Psychology
                Cognitive Psychology
                Language
                Science Policy
                Research Funding
                Government Funding of Science
                Computer and Information Sciences
                Data Management
                Metadata
                Social Sciences
                Economics
                Finance
                Computer and Information Sciences
                Artificial Intelligence
                Machine Learning
                Support Vector Machines
                Research and Analysis Methods
                Scientific Publishing
                Custom metadata
                The complete database which was used for all figures in the manuscript is available at https://zenodo.org/record/4679875. Code for PreprintMatch is availabe at https://github.com/PeterEckmann1/preprint-match.

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