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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Identifying SARS-CoV-2 antiviral compounds by screening for small molecule inhibitors of nsp15 endoribonuclease
This article has 14 authors:Reviewed by ScreenIT
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A new Reproduction Index R i and its Usefulness for Germany’s Covid19-Data
This article has 1 author:Reviewed by ScreenIT
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Droplet digital RT-PCR to detect SARS-CoV-2 signature mutations of variants of concern in wastewater
This article has 6 authors:Reviewed by ScreenIT
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Prediction and Evolution of the Molecular Fitness of SARS-CoV-2 Variants: Introducing SpikePro
This article has 2 authors:Reviewed by ScreenIT
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SARS-CoV-2 501Y.V2 escapes neutralization by South African COVID-19 donor plasma
This article has 19 authors:Reviewed by ScreenIT
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Effect of increased alcohol consumption during COVID‐19 pandemic on alcohol‐associated liver disease: A modeling study
This article has 6 authors:Reviewed by ScreenIT
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SARS-CoV2 spike protein gene variants with N501T and G142D mutation–dominated infections in mink in the United States
This article has 2 authors:Reviewed by ScreenIT
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Identification of lectin receptors for conserved SARS‐CoV‐2 glycosylation sites
This article has 25 authors:Reviewed by ScreenIT
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501Y.V2 and 501Y.V3 variants of SARS-CoV-2 lose binding to Bamlanivimab in vitro
This article has 13 authors:Reviewed by ScreenIT
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Rapid adaptation of SARS-CoV-2 in BALB/c mice: Novel mouse model for vaccine efficacy
This article has 31 authors:Reviewed by ScreenIT