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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Explaining the effective reproduction number of COVID-19 through mobility and enterprise statistics: Evidence from the first wave in Japan
This article has 2 authors:Reviewed by ScreenIT
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Increased resistance of SARS-CoV-2 variant P.1 to antibody neutralization
This article has 11 authors:Reviewed by ScreenIT
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Preliminary report on severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) Spike mutation T478K
This article has 4 authors:Reviewed by ScreenIT
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Factors associated with development of symptomatic disease in Ethiopian COVID-19 patients: a case-control study
This article has 12 authors:Reviewed by ScreenIT
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The synchronicity of COVID-19 disparities: Statewide epidemiologic trends in SARS-CoV-2 morbidity, hospitalization, and mortality among racial minorities and in rural America
This article has 6 authors:Reviewed by ScreenIT
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Evaluation of the Panbio™ COVID-19 ag rapid test at an emergency room in a hospital in São Paulo, Brazil
This article has 6 authors:Reviewed by ScreenIT
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Serological Profile Of Specific Antibodies Against Dominant Antigens Of SARS-CoV-2 In Chilean COVID-19 Patients.
This article has 10 authors:Reviewed by ScreenIT
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Exploration of interethnic variation and repurposed drug efficacy in the treatment of SARS-CoV-2 Infection (COVID-19)
This article has 1 author:Reviewed by ScreenIT
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Forecasting the Spreading Trajectory of the COVID-19 Pandemic
This article has 2 authors:Reviewed by ScreenIT
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Chimeric spike mRNA vaccines protect against Sarbecovirus challenge in mice
This article has 17 authors:Reviewed by ScreenIT