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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Epidemic Landscape and Forecasting of SARS-CoV-2 in India
This article has 9 authors:Reviewed by ScreenIT
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Clinical characteristics of children with COVID-19: a rapid review and meta-analysis
This article has 19 authors:Reviewed by ScreenIT
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Application of telemedicine during the coronavirus disease epidemics: a rapid review and meta-analysis
This article has 20 authors:Reviewed by ScreenIT
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Potential effectiveness and safety of antiviral agents in children with coronavirus disease 2019: a rapid review and meta-analysis
This article has 20 authors:Reviewed by ScreenIT
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Association of inflammatory markers with the severity of COVID-19: A meta-analysis
This article has 7 authors:Reviewed by ScreenIT
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Efficacy and safety of antibiotic agents in children with COVID-19: a rapid review
This article has 17 authors:Reviewed by ScreenIT
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CoroNet: A Deep Network Architecture for Semi-Supervised Task-Based Identification of COVID-19 from Chest X-ray Images
This article has 3 authors:Reviewed by ScreenIT
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A systematic review of antibody mediated immunity to coronaviruses: kinetics, correlates of protection, and association with severity
This article has 17 authors:Reviewed by ScreenIT
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Links between air pollution and COVID-19 in England
This article has 6 authors:Reviewed by ScreenIT
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Open Development and Clinical Validation of Multiple 3D-Printed Nasopharyngeal Collection Swabs: Rapid Resolution of a Critical COVID-19 Testing Bottleneck
This article has 13 authors:Reviewed by ScreenIT