ScreenIT
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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Currently prescribed drugs in the UK that could upregulate or downregulate ACE2 in COVID-19 disease: a systematic review
This article has 8 authors:Reviewed by ScreenIT
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Predicting COVID-19 spread in the face of control measures in West Africa
This article has 5 authors:Reviewed by ScreenIT
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Retrospective analysis of high flow nasal therapy in COVID-19-related moderate-to-severe hypoxaemic respiratory failure
This article has 17 authors:Reviewed by ScreenIT
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Evaluation of ELISA tests for the qualitative determination of IgG, IgM and IgA to SARS-CoV-2
This article has 12 authors:Reviewed by ScreenIT
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SARS-CoV-2 IgG antibody responses in New York City
This article has 5 authors:Reviewed by ScreenIT
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Hasty Reduction of COVID-19 Lockdown Measures Leads to the Second Wave of Infection
This article has 3 authors:Reviewed by ScreenIT
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Diagnostic performance of CT and its key signs for COVID-19: A systematic review and meta-analysis
This article has 5 authors:Reviewed by ScreenIT
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Estimating effective reproduction number using generation time versus serial interval, with application to COVID-19 in the Greater Toronto Area, Canada
This article has 2 authors:Reviewed by ScreenIT
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COVID ‐19: Impact of obesity and diabetes on disease severity
This article has 5 authors:Reviewed by ScreenIT
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Patient Trajectories Among Persons Hospitalized for COVID-19
This article has 28 authors:Reviewed by ScreenIT