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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Data Sharing in Southeast Asia During the First Wave of the COVID-19 Pandemic
This article has 4 authors:Reviewed by ScreenIT
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Viral Dynamics Matter in COVID-19 Pneumonia: the success of early treatment with hydroxychloroquine and azithromycin in Lebanon
This article has 10 authors:Reviewed by ScreenIT
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Seroprevalence of SARS-CoV-2 in slums versus non-slums in Mumbai, India
This article has 11 authors: -
Role of FYVE and Coiled-Coil Domain Autophagy Adaptor 1 in severity of COVID-19 infection
This article has 5 authors:Reviewed by ScreenIT
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The SARS-CoV-2 Spike mutation D614G increases entry fitness across a range of ACE2 levels, directly outcompetes the wild type, and is preferentially incorporated into trimers
This article has 3 authors:Reviewed by ScreenIT
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Viable virus aerosol propagation by positive airway pressure circuit leak and mitigation with a ventilated patient hood
This article has 8 authors:Reviewed by ScreenIT
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Estimation of COVID-19 outbreak size in Italy based on international case exportations
This article has 4 authors:Reviewed by ScreenIT
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Epidemiology of Severe Acute Respiratory Syndrome Coronavirus 2 Emergence Amidst Community-Acquired Respiratory Viruses
This article has 18 authors:Reviewed by ScreenIT
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Evaluation of filtration effectiveness of various types of facemasks following with different sterilization methods
This article has 5 authors:Reviewed by ScreenIT
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Isolation of infected people and their contacts is likely to be effective against many short-term epidemics
This article has 2 authors:Reviewed by ScreenIT