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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Early estimates of SARS-CoV-2 B.1.1.7 variant emergence in a university setting
This article has 7 authors:Reviewed by ScreenIT
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Biochemical characterization of protease activity of Nsp3 from SARS-CoV-2 and its inhibition by nanobodies
This article has 18 authors:Reviewed by ScreenIT
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Fueling the Covid-19 pandemic: summer school holidays and incidence rates in German districts
This article has 2 authors:Reviewed by ScreenIT
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Rapid characterization of spike variants via mammalian cell surface display
This article has 18 authors:Reviewed by ScreenIT
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Mental health problems among Dutch adolescents of the general population before and 9 months after the COVID-19 outbreak: A longitudinal cohort study
This article has 3 authors:Reviewed by ScreenIT
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Controlling the pandemic during the SARS-CoV-2 vaccination rollout
This article has 8 authors:Reviewed by ScreenIT
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D614G mutation in the SARS-CoV-2 spike protein enhances viral fitness by desensitizing it to temperature-dependent denaturation
This article has 4 authors:Reviewed by ScreenIT
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COVID-19 vaccine acceptance in older Syrian refugees: Preliminary findings from an ongoing study
This article has 7 authors:Reviewed by ScreenIT
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Severe COVID-19 patients display a back boost of seasonal coronavirus-specific antibodies
This article has 14 authors:Reviewed by ScreenIT
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Tafenoquine inhibits replication of SARS-Cov-2 at pharmacologically relevant concentrations in vitro
This article has 6 authors:Reviewed by ScreenIT