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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Genetically proxied interleukin-6 receptor inhibition: opposing associations with COVID-19 and pneumonia
This article has 3 authors:Reviewed by ScreenIT
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Durable SARS-CoV-2 B cell immunity after mild or severe disease
This article has 16 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Analytic comparison between three high-throughput commercial SARS-CoV-2 antibody assays reveals minor discrepancies in a high-incidence population
This article has 24 authors:Reviewed by ScreenIT
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Patterns of within-host genetic diversity in SARS-CoV-2
This article has 41 authors:This article has been curated by 1 group: -
A modelling analysis of the effectiveness of second wave COVID-19 response strategies in Australia
This article has 6 authors:Reviewed by ScreenIT
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ACE2 Is Expressed in Immune Cells That Infiltrate the Placenta in Infection-Associated Preterm Birth
This article has 10 authors:Reviewed by ScreenIT
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Rapid evaluation of neutralizing antibodies in COVID-19 patients
This article has 20 authors:Reviewed by ScreenIT
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Infection fatality risk for SARS-CoV-2 in community dwelling population of Spain: nationwide seroepidemiological study
This article has 19 authors:Reviewed by ScreenIT
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Long-Term Persistence of Spike Antibody and Predictive Modeling of Antibody Dynamics Following Infection with SARS-CoV-2
This article has 18 authors:Reviewed by ScreenIT
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Country specific mutational profile of SARS-CoV-2 in pre- and post-international travel ban: Effect on vaccine efficacy
This article has 2 authors:Reviewed by ScreenIT