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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SARS-CoV-2 Seroprevalence after Third Wave of Infections, South Africa
This article has 20 authors:Reviewed by ScreenIT
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Strength and durability of antibody responses to BNT162b2 and CoronaVac
This article has 13 authors:Reviewed by ScreenIT
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Workplace infection control measures and romantic activities of workers during COVID-19 pandemic: A prospective cohort study in Japan
This article has 9 authors:Reviewed by ScreenIT
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Comprehensive humoral and cellular immune responses to SARS-CoV-2 variants in diverse Chinese populations: A benefit perspective of national vaccination
This article has 23 authors:Reviewed by ScreenIT
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Favipiravir, lopinavir-ritonavir or combination therapy (FLARE): a randomised, double blind, 2x2 factorial placebo-controlled trial of early antiviral therapy in COVID-19
This article has 18 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Summarizing Study Characteristics and Diagnostic Performance of Commercially Available Tests for Respiratory Syncytial Virus: A Scoping Literature Review in the COVID-19 Era
This article has 5 authors:Reviewed by ScreenIT
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Direct and indirect mortality impacts of the COVID-19 pandemic in the United States, March 1, 2020 to January 1, 2022
This article has 7 authors:This article has been curated by 1 group: -
Omicron Spike Protein Has a Positive Electrostatic Surface That Promotes ACE2 Recognition and Antibody Escape
This article has 4 authors:Reviewed by ScreenIT
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Dam–Infant Rhesus Macaque Pairs to Dissect Age-Dependent Responses to SARS-CoV-2 Infection
This article has 21 authors:Reviewed by ScreenIT
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Molecular dynamics simulations of the spike trimeric ectodomain of the SARS-CoV-2 Omicron variant: structural relationships with infectivity, evasion to immune system and transmissibility
This article has 4 authors:Reviewed by ScreenIT