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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Opening Schools and Trends in SARS-CoV-2 Transmission in European Countries
This article has 11 authors:Reviewed by ScreenIT
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Vaccine effectiveness of the first dose of ChAdOx1 nCoV-19 and BNT162b2 against SARS-CoV-2 infection in residents of long-term care facilities in England (VIVALDI): a prospective cohort study
This article has 15 authors:Reviewed by ScreenIT
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SARS-CoV-2 within-host diversity and transmission
This article has 38 authors:Reviewed by ScreenIT
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Identifiability and predictability of integer- and fractional-order epidemiological models using physics-informed neural networks
This article has 6 authors:Reviewed by ScreenIT
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An ancient viral epidemic involving host coronavirus interacting genes more than 20,000 years ago in East Asia
This article has 10 authors:Reviewed by ScreenIT
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A novel conformational state for SARS-CoV-2 main protease
This article has 11 authors:Reviewed by ScreenIT
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Efficacy and breadth of adjuvanted SARS-CoV-2 receptor-binding domain nanoparticle vaccine in macaques
This article has 57 authors:Reviewed by ScreenIT
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Scalable, Micro-Neutralization Assay for Assessment of SARS-CoV-2 (COVID-19) Virus-Neutralizing Antibodies in Human Clinical Samples
This article has 14 authors:Reviewed by ScreenIT
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Trends of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody prevalence in selected regions across Ghana
This article has 25 authors:Reviewed by ScreenIT
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Rapid, inexpensive methods for exploring SARS CoV-2 D614G mutation
This article has 3 authors:Reviewed by ScreenIT