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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NSAID use and clinical outcomes in COVID-19 patients: a 38-center retrospective cohort study
This article has 23 authors:Reviewed by ScreenIT
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Development of Spike Receptor-Binding Domain Nanoparticles as a Vaccine Candidate against SARS-CoV-2 Infection in Ferrets
This article has 12 authors:Reviewed by ScreenIT
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Effect of multiple freeze–thaw cycles on the detection of anti-SARS-CoV-2 IgG antibodies
This article has 10 authors:Reviewed by ScreenIT
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SARS-CoV-2 spike protein S1 induces fibrin(ogen) resistant to fibrinolysis: implications for microclot formation in COVID-19
This article has 9 authors:Reviewed by ScreenIT
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The new SARS-CoV-2 variant and reinfection in the resurgence of COVID-19 outbreaks in Manaus, Brazil
This article has 5 authors:Reviewed by ScreenIT
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SARS-CoV-2 genomic characterization and clinical manifestation of the COVID-19 outbreak in Uruguay
This article has 25 authors:Reviewed by ScreenIT
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Versatile live-attenuated SARS-CoV-2 vaccine platform applicable to variants induces protective immunity
This article has 14 authors:Reviewed by ScreenIT
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Structure and dynamics of SARS-CoV-2 proofreading exoribonuclease ExoN
This article has 9 authors:Reviewed by ScreenIT
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Association of CXCR6 with COVID-19 severity: delineating the host genetic factors in transcriptomic regulation
This article has 6 authors:Reviewed by ScreenIT
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Complete map of SARS-CoV-2 RBD mutations that escape the monoclonal antibody LY-CoV555 and its cocktail with LY-CoV016
This article has 4 authors:Reviewed by ScreenIT