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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Dynamics of competing SARS-CoV-2 variants during the Omicron epidemic in England
This article has 19 authors:Reviewed by ScreenIT
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Consistency of covid-19 trial preprints with published reports and impact for decision making: retrospective review
This article has 19 authors:Reviewed by ScreenIT
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Differential Pathogenesis of SARS-CoV-2 Variants of Concern in Human ACE2-Expressing Mice
This article has 9 authors:Reviewed by ScreenIT
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Vaccine-induced immune thrombotic thrombocytopenia is mediated by a stereotyped clonotypic antibody
This article has 9 authors:Reviewed by ScreenIT
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A simple algorithm based on initial Ct values predicts the duration to SARS-CoV-2 negativity and allows more efficient test-to-release and return-to-work schedules
This article has 3 authors:Reviewed by ScreenIT
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Estimating the number of breakthrough COVID-19 deaths in the United States
This article has 1 author:Reviewed by ScreenIT
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Clinical Variables Correlate with Serum Neutralizing Antibody Titers after COVID-19 mRNA Vaccination in an Adult, US-based Population
This article has 16 authors:Reviewed by ScreenIT
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Biochemical, biophysical, and immunological characterization of respiratory secretions in severe SARS-CoV-2 infections
This article has 26 authors:Reviewed by ScreenIT
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Significant impacts of the COVID-19 pandemic on race/ethnic differences in US mortality
This article has 4 authors:Reviewed by ScreenIT
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Cardiac impairment in Long Covid 1-year post SARS-CoV-2 infection
This article has 15 authors:Reviewed by ScreenIT