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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Sex differences in the mortality rate for coronavirus disease 2019 compared to other causes of death: an analysis of population-wide data from 63 countries
This article has 6 authors:Reviewed by ScreenIT
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Phase 1 randomized trial of a plant-derived virus-like particle vaccine for COVID-19
This article has 19 authors:Reviewed by ScreenIT
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Temperature effect on the SARS-CoV-2: A molecular dynamics study of the spike homotrimeric glycoprotein
This article has 5 authors:Reviewed by ScreenIT
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Tocilizumab in Patients Hospitalized with Covid-19 Pneumonia
This article has 20 authors:Reviewed by ScreenIT
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COVID-19 Excess Deaths in the United States, New York City, and Michigan During April 2020
This article has 2 authors:Reviewed by ScreenIT
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Error rates in SARS-CoV-2 testing examined with Bayes' theorem
This article has 1 author:Reviewed by ScreenIT
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sMAdCAM: IL-6 Ratio Influences Disease Progression and Anti-Viral Responses in SARS-CoV-2 Infection
This article has 20 authors:Reviewed by ScreenIT
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Conformational Ensembles of Noncoding Elements in the SARS-CoV-2 Genome from Molecular Dynamics Simulations
This article has 3 authors:Reviewed by ScreenIT
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Evaluation of at-home methods for N95 filtering facepiece respirator decontamination
This article has 10 authors:Reviewed by ScreenIT
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OPTIMIZING COVID-19 VACCINE USAGE
This article has 3 authors:Reviewed by ScreenIT