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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Rapid SARS-CoV-2 Adaptation to Available Cellular Proteases
This article has 12 authors:Reviewed by ScreenIT
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The scale and dynamics of COVID-19 epidemics across Europe
This article has 4 authors:Reviewed by ScreenIT
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Are the upper bounds for new SARS-CoV-2 infections in Germany useful?
This article has 4 authors:Reviewed by ScreenIT
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Pharmacologic profiling reveals lapatinib as a novel antiviral against SARS-CoV-2 in vitro
This article has 12 authors:Reviewed by ScreenIT
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Dynamic modelling to identify mitigation strategies for the COVID-19 pandemic
This article has 5 authors:Reviewed by ScreenIT
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Seroprevalence of anti-SARS-CoV-2 IgG antibodies, risk factors for infection and associated symptoms in Geneva, Switzerland: a population-based study
This article has 20 authors:Reviewed by ScreenIT
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Forecasting sub-national trends in COVID-19 vaccine uptake in the UK
This article has 1 author:Reviewed by ScreenIT
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How closely is COVID-19 related to HCoV, SARS, and MERS? : Clinical comparison of coronavirus infections and identification of risk factors influencing the COVID-19 severity using common data model (CDM)
This article has 4 authors:Reviewed by ScreenIT
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Voxel-level forecast system for lesion development in patients with COVID-19
This article has 11 authors:Reviewed by ScreenIT
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Failures of quarantine systems for preventing COVID‐19 outbreaks in Australia and New Zealand
This article has 8 authors:Reviewed by ScreenIT