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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Targeting the Conserved Stem Loop 2 Motif in the SARS-CoV-2 Genome
This article has 18 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Oral Delivery of SARS-CoV-2 DNA Vaccines Using Attenuated Salmonella typhimurium as a Carrier in Rat
This article has 10 authors:Reviewed by ScreenIT
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School and community reopening during the COVID-19 pandemic: a mathematical modelling study
This article has 10 authors:Reviewed by ScreenIT
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Evaluation of Safety and Immunogenicity of an Adjuvanted, TH-1 Skewed, Whole Virion InactivatedSARS-CoV-2 Vaccine - BBV152
This article has 22 authors:Reviewed by ScreenIT
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5-amino levulinic acid inhibits SARS-CoV-2 infection in vitro
This article has 9 authors:Reviewed by ScreenIT
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Fighting COVID-19 with Flexible Testing: Models and Insights
This article has 2 authors:Reviewed by ScreenIT
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Mental health symptoms in a cohort of hospital healthcare workers following the first peak of the COVID-19 pandemic in the UK
This article has 10 authors:Reviewed by ScreenIT
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Exhaled SARS-CoV-2 quantified by face-mask sampling in hospitalised patients with COVID-19
This article has 17 authors:Reviewed by ScreenIT
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COVID-19 Severity Is Associated with Differential Antibody Fc-Mediated Innate Immune Functions
This article has 16 authors:Reviewed by ScreenIT
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Mouthwashes with CPC Reduce the Infectivity of SARS-CoV-2 Variants In Vitro
This article has 12 authors:Reviewed by ScreenIT