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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Post-Disease Divergence in SARS-CoV-2 RNA Detection between Nasopharyngeal, Anterior Nares and Saliva/Oral Fluid Specimens - Significant Implications for Policy & Public Health
This article has 14 authors:Reviewed by ScreenIT
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Decay of Fc-dependent antibody functions after mild to moderate COVID-19
This article has 16 authors:Reviewed by ScreenIT
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Evolution and variation of 2019-novel coronavirus
This article has 4 authors:Reviewed by ScreenIT
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Analysis and Forecast of COVID-19 Pandemic in Pakistan
This article has 1 author:Reviewed by ScreenIT
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The excess insulin requirement in severe COVID‐19 compared to non‐COVID‐19 viral pneumonitis is related to the severity of respiratory failure and pre‐existing diabetes
This article has 9 authors:Reviewed by ScreenIT
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A Systematic Review of the Incubation Period of SARS-CoV-2: The Effects of Age, Biological Sex, and Location on Incubation Period
This article has 3 authors: -
Does Proton Pump Inhibitor Use Lead to a Higher Risk of Coronavirus Disease 2019 Infection and Progression to Severe Disease? a Meta-analysis
This article has 13 authors:Reviewed by ScreenIT
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Complete genome characterisation of a novel coronavirus associated with severe human respiratory disease in Wuhan, China
This article has 19 authors:Reviewed by ScreenIT
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Clinical characteristics and epidemiology survey of lung transplantation recipients accepting surgeries during the COVID-19 pandemic : from area near Hubei Province
This article has 10 authors:Reviewed by ScreenIT
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Spatial and temporal regularization to estimate COVID-19 reproduction number R(t): Promoting piecewise smoothness via convex optimization
This article has 10 authors:Reviewed by ScreenIT