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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Estimating Impact of Austerity policies in COVID-19 fatality rates: Examining the dynamics of economic policy and Case Fatality Rates (CFR) of COVID-19 in OECD countries
This article has 1 author:Reviewed by ScreenIT
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Hidden periods, duration and final size of COVID-19 pandemic
This article has 1 author:Reviewed by ScreenIT
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On the timing of interventions to preserve hospital capacity: lessons to be learned from the Belgian SARS-CoV-2 pandemic in 2020
This article has 3 authors:Reviewed by ScreenIT
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Structural impact on SARS-CoV-2 spike protein by D614G substitution
This article has 13 authors:Reviewed by ScreenIT
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Modelling and analysis of COVID-19 epidemic in India
This article has 1 author:Reviewed by ScreenIT
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Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population
This article has 5 authors:Reviewed by ScreenIT
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Tracking and forecasting milepost moments of the epidemic in the early-outbreak: framework and applications to the COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Low-impact social distancing interventions to mitigate local epidemics of SARS-CoV-2
This article has 1 author:Reviewed by ScreenIT
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Easing social distancing index after COVID-19 pandemic
This article has 5 authors:Reviewed by ScreenIT
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Repeated cross-sectional sero-monitoring of SARS-CoV-2 in New York City
This article has 17 authors:Reviewed by ScreenIT