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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Ivermectin shows clinical benefits in mild to moderate COVID19: a randomized controlled double-blind, dose-response study in Lagos
This article has 10 authors:Reviewed by ScreenIT
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Corticosteroid treatment has no effect on hospital mortality in COVID-19 patients
This article has 12 authors:Reviewed by ScreenIT
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An improved mathematical prediction of the time evolution of the Covid-19 pandemic in Italy, with a Monte Carlo simulation and error analyses
This article has 2 authors:Reviewed by ScreenIT
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Large-scale silane bead-based SARS-CoV-2 testing of a nursing home in Spain identifies a viral reservoir during lockdown period
This article has 18 authors:Reviewed by ScreenIT
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Simulation-based study of COVID-19 outbreak associated with air-conditioning in a restaurant
This article has 4 authors:Reviewed by ScreenIT
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Early pandemic molecular diversity of SARS-CoV-2 in children
This article has 14 authors:Reviewed by ScreenIT
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Distinguishing between direct and indirect consequences of covid-19
This article has 13 authors:Reviewed by ScreenIT
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QT Interval Prolongation in Patients Treated for COVID-19
This article has 6 authors:Reviewed by ScreenIT
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Generation of glucocorticoid-resistant SARS-CoV-2 T cells for adoptive cell therapy
This article has 34 authors:Reviewed by ScreenIT
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Molecular Architecture of Early Dissemination and Massive Second Wave of the SARS-CoV-2 Virus in a Major Metropolitan Area
This article has 25 authors: