ScreenIT
The Automated Screening Working Groups is a group of software engineers and biologists passionate about improving scientific manuscripts on a large scale. Our members have created tools that check for common problems in scientific manuscripts, including information needed to improve transparency and reproducibility. We have combined our tools into a single pipeline, called ScreenIT. We're currently using our tools to screen COVID preprints.
Latest preprint reviews
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A Recombinant Subunit Vaccine Induces a Potent, Broadly Neutralizing, and Durable Antibody Response in Macaques against the SARS-CoV-2 P.1 (Gamma) Variant
This article has 17 authors:Reviewed by ScreenIT
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Caspase-4/11 exacerbates disease severity in SARS–CoV-2 infection by promoting inflammation and immunothrombosis
This article has 42 authors:Reviewed by ScreenIT
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LIGHTHOUSE illuminates therapeutics for a variety of diseases including COVID-19
This article has 8 authors:Reviewed by ScreenIT
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Screening key genes and signaling pathways in COVID-19 infection and its associated complications by integrated bioinformatics analysis
This article has 2 authors:Reviewed by ScreenIT
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Dynamics of Mask Use as a Prevention Strategy against SARS-CoV-2 in Panama
This article has 12 authors:Reviewed by ScreenIT
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Effectiveness of vaccination in preventing severe SARS CoV-2 infection in South India-a hospital-based cross-sectional study
This article has 3 authors:Reviewed by ScreenIT
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Profiles of US Hispanics Unvaccinated for COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Factors associated with an increased risk of SARS-CoV-2 infection in healthcare workers in aerosol-generating disciplines
This article has 18 authors:Reviewed by ScreenIT
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COVID-19 Vaccine Hesitancy in India: An Exploratory Analysis
This article has 2 authors:Reviewed by ScreenIT
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University patenting and licensing practices in the United Kingdom during the first year of the COVID-19 pandemic
This article has 4 authors:Reviewed by ScreenIT