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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WIN 55,212-2 shows anti-inflammatory and survival properties in human iPSC-derived cardiomyocytes infected with SARS-CoV-2
This article has 27 authors:Reviewed by ScreenIT
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Association between oral anticoagulants and COVID-19-related outcomes: a population-based cohort study
This article has 31 authors:Reviewed by ScreenIT
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SARS-CoV-2 RNA detected in urban wastewater from Porto, Portugal: Method optimization and continuous 25-week monitoring
This article has 8 authors:Reviewed by ScreenIT
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SARS-CoV-2 N gene dropout and N gene Ct value shift as indicator for the presence of B.1.1.7 lineage in a commercial multiplex PCR assay
This article has 13 authors:Reviewed by ScreenIT
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The ongoing evolution of variants of concern and interest of SARS-CoV-2 in Brazil revealed by convergent indels in the amino (N)-terminal domain of the spike protein
This article has 37 authors:Reviewed by ScreenIT
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Inhibition mechanism of SARS-CoV-2 main protease by ebselen and its derivatives
This article has 12 authors:Reviewed by ScreenIT
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Interactions of SARS-CoV-2 envelope protein with amilorides correlate with antiviral activity
This article has 12 authors:Reviewed by ScreenIT
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Quantifying contact patterns in response to COVID-19 public health measures in Canada
This article has 7 authors:Reviewed by ScreenIT
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Antibody Responses in Elderly Residential Care Persons following COVID-19 mRNA Vaccination
This article has 10 authors:Reviewed by ScreenIT
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Subgenomic RNAs as molecular indicators of asymptomatic SARS-CoV-2 infection
This article has 14 authors:Reviewed by ScreenIT