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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Structural basis for the inhibition of the papain-like protease of SARS-CoV-2 by small molecules
This article has 15 authors:Reviewed by ScreenIT
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A Systematic Review and Network Meta-Analysis for COVID-19 Treatments
This article has 4 authors:Reviewed by ScreenIT
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Sars-Cov-2 in Argentina: Following Virus Spreading Using Granger Causality
This article has 1 author:Reviewed by ScreenIT
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A COVID-19 transmission model informing medication development and supply chain needs
This article has 8 authors:Reviewed by ScreenIT
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Personal protective equipment for reducing the risk of COVID-19 infection among health care workers involved in emergency trauma surgery during the pandemic: An umbrella review
This article has 5 authors:Reviewed by ScreenIT
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Factors Associated with COVID-19 Mitigation Behavior among US Adults
This article has 2 authors:Reviewed by ScreenIT
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A Covid-19 case mortality rate without time delay systematics
This article has 3 authors:Reviewed by ScreenIT
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Unsupervised clustering analysis of SARS-Cov-2 population structure reveals six major subtypes at early stage across the world
This article has 4 authors:Reviewed by ScreenIT
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Forecasting COVID-19 impact on hospital bed-days, ICU-days, ventilator-days and deaths by US state in the next 4 months
This article has 2 authors:Reviewed by ScreenIT
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Prevalence of SARS-CoV-2 antibodies in France: results from nationwide serological surveillance
This article has 23 authors:Reviewed by ScreenIT