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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Macrolevel association of COVID-19 with non-communicable disease risk factors in India
This article has 6 authors:Reviewed by ScreenIT
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Maturation and persistence of the anti-SARS-CoV-2 memory B cell response
This article has 24 authors:Reviewed by ScreenIT
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Cognitive and mental health changes and their vulnerability factors related to COVID-19 lockdown in Italy
This article has 4 authors:Reviewed by ScreenIT
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Virological assessment of hospitalized patients with COVID-2019
This article has 18 authors:Reviewed by ScreenIT
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Retinol Depletion in COVID-19
This article has 5 authors:Reviewed by ScreenIT
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Underdetection of cases of COVID-19 in France threatens epidemic control
This article has 17 authors:Reviewed by ScreenIT
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Dried Blood Spot as an Alternative to Plasma/Serum for SARS-CoV-2 IgG Detection, an Opportunity to Be Sized to Facilitate COVID-19 Surveillance Among Schoolchildren
This article has 11 authors:Reviewed by ScreenIT
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Cardiorespiratory Fitness and Neuromuscular Performance in Patients Recovered from COVID-19
This article has 9 authors:Reviewed by ScreenIT
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Predictive accuracy of a hierarchical logistic model of cumulative SARS-CoV-2 case growth until May 2020
This article has 1 author:Reviewed by ScreenIT
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First Report on the Latvian SARS-CoV-2 Isolate Genetic Diversity
This article has 21 authors:Reviewed by ScreenIT