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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Remdesivir Metabolite GS-441524 Effectively Inhibits SARS-CoV-2 Infection in Mouse Models
This article has 16 authors:Reviewed by ScreenIT
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Huge Excess Mortality Due to the Delta Strain of COVID-19 in Japan in August 2021
This article has 5 authors:Reviewed by ScreenIT
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COVID-HEART: Development and Validation of a Multi-Variable Model for Real-Time Prediction of Cardiovascular Complications in Hospitalized Patients with COVID-19
This article has 9 authors:Reviewed by ScreenIT
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Burden of nosocomial COVID-19 in Wales: results from a multicentre retrospective observational study of 2508 hospitalised adults
This article has 13 authors:Reviewed by ScreenIT
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DINC-COVID: A webserver for ensemble docking with flexible SARS-CoV-2 proteins
This article has 6 authors:Reviewed by ScreenIT
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Early epidemic spread, percolation and Covid-19
This article has 1 author:Reviewed by ScreenIT
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Convalescent Plasma for Patients With Severe Coronavirus Disease 2019 (COVID-19): A Matched Cohort Study
This article has 12 authors:Reviewed by ScreenIT
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Outcomes of Percutaneous Tracheostomy for Patients With SARS-CoV-2 Respiratory Failure
This article has 10 authors:Reviewed by ScreenIT
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Topography, Spike Dynamics, and Nanomechanics of Individual Native SARS-CoV-2 Virions
This article has 4 authors:Reviewed by ScreenIT
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Phosphate levels and pulmonary damage in COVID-19 patients based on CO-RADS scheme: is there any link between parathyroid gland and COVID-19?
This article has 11 authors:Reviewed by ScreenIT