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 Delta variant induces enhanced pathology and inflammatory responses in K18-hACE2 mice
This article has 18 authors:Reviewed by ScreenIT
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The value of vaccine booster doses to mitigate the global impact of the Omicron SARS-CoV-2 variant
This article has 11 authors:Reviewed by ScreenIT
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ASGR1 is a candidate receptor for SARS-CoV-2 that promotes infection of liver cells
This article has 18 authors:Reviewed by ScreenIT
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Modelling how the altered usage of cell entry pathways by the SARS-CoV-2 Omicron variant may affect the efficacy and synergy of TMPRSS2 and Cathepsin B/L inhibitors
This article has 2 authors:Reviewed by ScreenIT
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Immunokinetic Model for COVID-19 Patients
This article has 3 authors:Reviewed by ScreenIT
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Mucociliary transport deficiency and disease progression in Syrian hamsters with SARS-CoV-2 infection
This article has 26 authors:Reviewed by ScreenIT
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RASCL: Rapid Assessment Of SARS-CoV-2 Clades Through Molecular Sequence Analysis
This article has 8 authors:Reviewed by ScreenIT
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Second Climate Survey of Biomedical PhD Students in the Time of Covid
This article has 2 authors:Reviewed by ScreenIT
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Omicron-associated changes in SARS-CoV-2 symptoms in the United Kingdom
This article has 16 authors:Reviewed by ScreenIT
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Selection analysis identifies unusual clustered mutational changes in Omicron lineage BA.1 that likely impact Spike function
This article has 39 authors:Reviewed by ScreenIT