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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Neurological Disorders Associated With COVID-19 Hospital Admissions: Experience of a Single Tertiary Healthcare Center
This article has 8 authors:Reviewed by ScreenIT
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Onset, duration and unresolved symptoms, including smell and taste changes, in mild COVID-19 infection: a cohort study in Israeli patients
This article has 8 authors:Reviewed by ScreenIT
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Ad26 vector-based COVID-19 vaccine encoding a prefusion-stabilized SARS-CoV-2 Spike immunogen induces potent humoral and cellular immune responses
This article has 24 authors:Reviewed by ScreenIT
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Evaluation of NGS-based approaches for SARS-CoV-2 whole genome characterisation
This article has 13 authors:Reviewed by ScreenIT
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An Examination of COVID-19 Mitigation Efficiency among 23 Countries
This article has 4 authors:Reviewed by ScreenIT
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Susceptibility-weighted imaging reveals cerebral microvascular injury in severe COVID-19
This article has 23 authors:Reviewed by ScreenIT
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Calibrating an Epidemic Compartment Model to Seroprevalence Survey Data
This article has 1 author:Reviewed by ScreenIT
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Analysis of meteorological conditions and prediction of epidemic trend of 2019-nCoV infection in 2020
This article has 8 authors:Reviewed by ScreenIT
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Timing of convalescent plasma administration and 28-day mortality in COVID-19 pneumonia
This article has 10 authors:Reviewed by ScreenIT
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Detections and SIR simulations of the COVID-19 pandemic waves in Ukraine
This article has 1 author:Reviewed by ScreenIT