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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Lymphopenia-induced T cell proliferation is a hallmark of severe COVID-19
This article has 16 authors:Reviewed by ScreenIT
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Increasing concentration of COVID-19 by socioeconomic determinants and geography in Toronto, Canada: an observational study
This article has 20 authors:Reviewed by ScreenIT
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Tocilizumab and Mortality in Hospitalised Patients with Covid-19. A Systematic Review Comparing Randomised Trials with Observational Studies
This article has 11 authors:Reviewed by ScreenIT
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Prevention and therapy of SARS-CoV-2 and the B.1.351 variant in mice
This article has 15 authors:Reviewed by ScreenIT
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Transition in learning approach for undergraduate medical students of Bangladesh in Covid 19 pandemic: A situation analysis
This article has 12 authors:Reviewed by ScreenIT
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Diagnostic accuracy and predictive value of clinical symptoms for the diagnosis of mild COVID-19
This article has 5 authors:Reviewed by ScreenIT
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Systematic review of the association between ABO blood type and COVID-19 incidence and mortality
This article has 3 authors:Reviewed by ScreenIT
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The Value of Rapid Antigen Tests for Identifying Carriers of Viable SARS-CoV-2
This article has 11 authors:Reviewed by ScreenIT
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The Effect of In-Person Primary and Secondary School Instruction on County-Level Severe Acute Respiratory Syndrome Coronavirus 2 Spread in Indiana
This article has 6 authors:Reviewed by ScreenIT
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Impact of a New SARS-CoV-2 Variant on the Population: A Mathematical Modeling Approach
This article has 3 authors:Reviewed by ScreenIT