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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Household transmission of SARS-CoV-2 from humans to pets in Washington and Idaho: burden and risk factors
This article has 14 authors:Reviewed by ScreenIT
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Public perception of COVID-19 vaccines through analysis of Twitter content and users
This article has 8 authors:Reviewed by ScreenIT
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Low Zinc Levels at Admission Associates with Poor Clinical Outcomes in SARS-CoV-2 Infection
This article has 16 authors:Reviewed by ScreenIT
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Registro argentino de manifestaciones neurológicas por coronavirus-19 (COVID-19)
This article has 45 authors:Reviewed by ScreenIT
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The Natural Stilbenoid (–)-Hopeaphenol Inhibits Cellular Entry of SARS-CoV-2 USA-WA1/2020, B.1.1.7, and B.1.351 Variants
This article has 14 authors:Reviewed by ScreenIT
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Brd4-bound enhancers drive cell-intrinsic sex differences in glioblastoma
This article has 13 authors:Reviewed by ScreenIT
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Comparing infectivity and virulence of emerging SARS-CoV-2 variants in Syrian hamsters
This article has 13 authors:Reviewed by ScreenIT
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Human Taste Cells Express ACE2: a Portal for SARS-CoV-2 Infection
This article has 6 authors:Reviewed by ScreenIT
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Brain Inflammation and Intracellular α-Synuclein Aggregates in Macaques after SARS-CoV-2 Infection
This article has 18 authors:Reviewed by ScreenIT
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Vaccine effectiveness after 1 st and 2 nd dose of the BNT162b2 mRNA Covid-19 Vaccine in long-term care facility residents and healthcare workers – a Danish cohort study
This article has 9 authors:Reviewed by ScreenIT