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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Prevention of COVID-19 by mRNA-based vaccines within the general population of California
This article has 8 authors:Reviewed by ScreenIT
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Revealing the Threat of Emerging SARS-CoV-2 Mutations to Antibody Therapies
This article has 4 authors:Reviewed by ScreenIT
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Estimating the asymptomatic proportion of SARS-CoV-2 infection in the general population: Analysis of nationwide serosurvey data in the Netherlands
This article has 9 authors:Reviewed by ScreenIT
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Detection of SARS-CoV-2 variant 501Y.V2 in Comoros Islands in January 2021
This article has 20 authors:Reviewed by ScreenIT
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Sex Differences in Lung Imaging and SARS-CoV-2 Antibody Responses in a COVID-19 Golden Syrian Hamster Model
This article has 30 authors:Reviewed by ScreenIT
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A randomized double-blind controlled trial of convalescent plasma in adults with severe COVID-19
This article has 42 authors:Reviewed by ScreenIT
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Nanotraps for the containment and clearance of SARS-CoV-2
This article has 19 authors:Reviewed by ScreenIT
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Identification of the most vulnerable populations in the psychosocial sphere: a cross-sectional study conducted in Catalonia during the strict lockdown imposed against the COVID-19 pandemic
This article has 13 authors:Reviewed by ScreenIT
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Compliance with Covid-19 measures: Evidence from New Zealand
This article has 3 authors:Reviewed by ScreenIT
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Acceptability of contact management and care of simple cases of COVID-19 at home: a cross-sectional study in Senegal
This article has 9 authors:Reviewed by ScreenIT