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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Household COVID-19 risk and in-person schooling
This article has 8 authors: -
Association of ABO blood group with COVID-19 severity, acute phase reactants and mortality
This article has 9 authors:Reviewed by ScreenIT
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Towards Understanding the COVID-19 Case Fatality Rate
This article has 3 authors:Reviewed by ScreenIT
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Improved Prediction of COVID-19 Transmission and Mortality Using Google Search Trends for Symptoms in the United States
This article has 6 authors:Reviewed by ScreenIT
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Assessing the impact of widespread respirator use in curtailing COVID-19 transmission in the USA
This article has 5 authors:Reviewed by ScreenIT
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A queuing model for ventilator capacity management during the COVID-19 pandemic
This article has 5 authors:Reviewed by ScreenIT
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Cardiac Surgery during the Covid-19 Pandemic: Evidence from the first wave
This article has 5 authors:Reviewed by ScreenIT
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A prefusion SARS-CoV-2 spike RNA vaccine is highly immunogenic and prevents lung infection in non-human primates
This article has 61 authors:Reviewed by ScreenIT
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“Ventilator-free days” composite outcome in patients with SARS-CoV-2 infection treated with tocilizumab: A retrospective competing risk analysis
This article has 9 authors:Reviewed by ScreenIT
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Enrichment of SARS-CoV-2 Entry Factors and Interacting Intracellular Genes in Tissue and Circulating Immune Cells
This article has 2 authors:Reviewed by ScreenIT