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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Human coronaviruses disassemble processing bodies
This article has 10 authors: -
Characterizing superspreading of SARS-CoV-2 : from mechanism to measurement
This article has 2 authors:Reviewed by ScreenIT
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Facemasks prevent influenza-like illness: implications for COVID-19
This article has 9 authors:Reviewed by ScreenIT
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Evolutionary dynamics of SARS‐CoV‐2 nucleocapsid protein and its consequences
This article has 9 authors:Reviewed by ScreenIT
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Interactions between SARS-CoV-2 and influenza, and the impact of coinfection on disease severity: a test-negative design
This article has 9 authors:Reviewed by ScreenIT
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Long-Term Exposure to Outdoor Air Pollution and COVID-19 Mortality: an ecological analysis in England
This article has 3 authors:Reviewed by ScreenIT
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Air pollution reduction and mortality benefit during the COVID-19 outbreak in China
This article has 5 authors:Reviewed by ScreenIT
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Pervasive transmission of E484K and emergence of VUI-NP13L with evidence of SARS-CoV-2 co-infection events by two different lineages in Rio Grande do Sul, Brazil
This article has 23 authors:Reviewed by ScreenIT
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On the Effect of Age on the Transmission of SARS-CoV-2 in Households, Schools, and the Community
This article has 3 authors:Reviewed by ScreenIT
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Mortality trends among hospitalised COVID-19 patients in Sweden: A nationwide observational cohort study
This article has 8 authors:Reviewed by ScreenIT