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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Ubiquitous Forbidden Order in R-group classified protein sequence of SARS-CoV-2 and other viruses
This article has 3 authors:Reviewed by ScreenIT
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Maternal health care services utilization amidstCOVID-19 pandemic in West Shoa zone, central Ethiopia
This article has 11 authors:Reviewed by ScreenIT
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COVID-19 is associated with new symptoms of multiple sclerosis that are prevented by disease modifying therapies
This article has 14 authors:Reviewed by ScreenIT
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Corticosteroids and mortality in patients with severe Covid-19 who have autoantibodies
This article has 8 authors:Reviewed by ScreenIT
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COVID-19–related anosmia is associated with viral persistence and inflammation in human olfactory epithelium and brain infection in hamsters
This article has 21 authors:Reviewed by ScreenIT
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Age-dependent appearance of SARS-CoV-2 entry sites in mouse chemosensory systems reflects COVID-19 anosmia-ageusia symptoms
This article has 7 authors:Reviewed by ScreenIT
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SARS-CoV-2 ORF6 disturbs nucleocytoplasmic trafficking to advance the viral replication
This article has 15 authors:Reviewed by ScreenIT
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Effects of Coronavirus Disease Pandemic on Tuberculosis Notifications, Malawi
This article has 14 authors:Reviewed by ScreenIT
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IL-1 Mediates Tissue-Specific Inflammation and Severe Respiratory Failure in COVID-19
This article has 12 authors:Reviewed by ScreenIT
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SARS-CoV-2 mutational cascades and the risk of hyper-exponential growth
This article has 4 authors:Reviewed by ScreenIT