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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Pre-pandemic mental health and disruptions to healthcare, economic and housing outcomes during the COVID-19 pandemic: evidence from 12 UK longitudinal studies
This article has 22 authors:Reviewed by ScreenIT
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Comparative analysis reveals the species-specific genetic determinants of ACE2 required for SARS-CoV-2 entry
This article has 20 authors:Reviewed by ScreenIT
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Sequelae in adults at 12 months after mild‐to‐moderate coronavirus disease 2019 (COVID‐19)
This article has 16 authors:Reviewed by ScreenIT
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SARS-CoV-2 variant with higher affinity to ACE2 shows reduced sera neutralization susceptibility
This article has 6 authors:Reviewed by ScreenIT
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Epitope profiling using computational structural modelling demonstrated on coronavirus-binding antibodies
This article has 6 authors:Reviewed by ScreenIT
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COVID-19-associated school closures and related efforts to sustain education and subsidized meal programs, United States, February 18–June 30, 2020
This article has 5 authors:Reviewed by ScreenIT
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SARS-CoV-2 serosurvey among adults involved in healthcare and health research in Guinea-Bissau, West Africa
This article has 10 authors:Reviewed by ScreenIT
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COVID-19 trends in Colombian regions with the highest disease burden
This article has 6 authors:Reviewed by ScreenIT
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SARS-CoV-2 3CLpro whole human proteome cleavage prediction and enrichment/depletion analysis
This article has 1 author:Reviewed by ScreenIT
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SARS-CoV-2 Quasispecies provides insight into its genetic dynamics during infection
This article has 16 authors:Reviewed by ScreenIT