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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Some Clinical and Immunological Features of Imported COVID-19 Cases in Mongolia
This article has 4 authors:Reviewed by ScreenIT
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Environmentally-induced mdig is a major contributor to the severity of COVID-19 through fostering expression of SARS-CoV-2 receptor NRPs and glycan metabolism
This article has 11 authors:Reviewed by ScreenIT
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Depression and anxiety among the University community during the Covid-19 pandemic: a study in Southern Brazil
This article has 7 authors:Reviewed by ScreenIT
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A statewide analysis of SARS-CoV-2 transmission in New York
This article has 10 authors:Reviewed by ScreenIT
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A novel variant of interest of SARS-CoV-2 with multiple spike mutations detected through travel surveillance in Africa
This article has 27 authors:Reviewed by ScreenIT
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Reflections of COVID-19 cases in the wastewater loading of SARS-CoV-2 RNA: A case of three major cities of Gujarat, India
This article has 5 authors:Reviewed by ScreenIT
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Natural spring water gargle and direct RT-PCR for the diagnosis of COVID-19 (COVID-SPRING study)
This article has 10 authors:Reviewed by ScreenIT
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Relation of severe COVID-19 in Scotland to transmission-related factors and risk conditions eligible for shielding support: REACT-SCOT case-control study
This article has 15 authors:Reviewed by ScreenIT
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Comparable seasonal pattern for COVID-19 and flu-like illnesses
This article has 2 authors:Reviewed by ScreenIT
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Timing the SARS-CoV-2 index case in Hubei province
This article has 5 authors:Reviewed by ScreenIT