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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Global seroprevalence of SARS-CoV-2 antibodies: A systematic review and meta-analysis
This article has 27 authors:Reviewed by ScreenIT
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High-throughput screening of the ReFRAME, Pandemic Box, and COVID Box drug repurposing libraries against SARS-CoV-2 nsp15 endoribonuclease to identify small-molecule inhibitors of viral activity
This article has 19 authors:Reviewed by ScreenIT
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Mitigating COVID-19 outbreaks in workplaces and schools by hybrid telecommuting
This article has 8 authors:Reviewed by ScreenIT
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Immuno-epidemiological life-history and the dynamics of SARS-CoV-2 over the next five years
This article has 9 authors:Reviewed by ScreenIT
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An attempt to optimize human resources allocation based on spatial diversity of the first wave of COVID–19 in Poland
This article has 3 authors:Reviewed by ScreenIT
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A Gaussian Model for the Time Development of the Sars-Cov-2 Corona Pandemic Disease. Predictions for Germany Made on 30 March 2020
This article has 2 authors:Reviewed by ScreenIT
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Mice with Induced Pulmonary Comorbidities Display Severe Lung Inflammation and Mortality following Exposure to SARS-CoV-2
This article has 29 authors:Reviewed by ScreenIT
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Indicators of recent COVID-19 infection status: findings from a large occupational cohort of staff and postgraduate research students from a UK university
This article has 13 authors:Reviewed by ScreenIT
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Utility of COVID-19 Decision Rules Related to Consecutive Decline in Positivity or Hospitalizations: A Data-driven Simulation Study
This article has 4 authors:Reviewed by ScreenIT
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The King’s College London Coronavirus Health and Experiences of Colleagues at King’s Study: SARS-CoV-2 antibody response in an occupational sample
This article has 8 authors:Reviewed by ScreenIT