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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Estimates and Determinants of SARS-Cov-2 Seroprevalence and Infection Fatality Ratio Using Latent Class Analysis: The Population-Based Tirschenreuth Study in the Hardest-Hit German County in Spring 2020
This article has 23 authors:Reviewed by ScreenIT
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COVID-19 risk perception and vaccine acceptance in individuals with chronic disease
This article has 4 authors:Reviewed by ScreenIT
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Statistical Design and Analysis of Diagnostic Tests for Mutating Viruses
This article has 6 authors:Reviewed by ScreenIT
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The interplay of policy, behavior, and socioeconomic conditions in early COVID-19 epidemiology in Georgia
This article has 3 authors:Reviewed by ScreenIT
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Changes in preterm birth and caesarean deliveries in the United States during the SARS‐CoV‐2 pandemic
This article has 6 authors:Reviewed by ScreenIT
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Covidex: an ultrafast and accurate tool for virus subtyping
This article has 4 authors:Reviewed by ScreenIT
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Hospital mortality in COVID-19 patients in Belgium treated with statins, ACE inhibitors and/or ARBs
This article has 12 authors:Reviewed by ScreenIT
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COVID-19 vaccine hesitancy in Addis Ababa, Ethiopia: a mixed-method study
This article has 9 authors:Reviewed by ScreenIT
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MMGB/SA Consensus Estimate of the Binding Free Energy Between the Novel Coronavirus Spike Protein to the Human ACE2 Receptor
This article has 2 authors:Reviewed by ScreenIT
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SARS-CoV-2 infection, disease and transmission in domestic cats
This article has 18 authors:Reviewed by ScreenIT