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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Genome Scale-Differential Flux Analysis reveals deregulation of lung cell metabolism on SARS-CoV-2 infection
This article has 2 authors:Reviewed by ScreenIT
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Clinical validation of automated and rapid mariPOC SARS-CoV-2 antigen test
This article has 8 authors:Reviewed by ScreenIT
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The Silent Pandemic COVID-19 in the Asymptomatic Population
This article has 2 authors:Reviewed by ScreenIT
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SARS‐CoV ‐2 in human milk is inactivated by Holder pasteurisation but not cold storage
This article has 8 authors:Reviewed by ScreenIT
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Potential impact of intervention strategies on COVID-19 transmission in Malawi: a mathematical modelling study
This article has 12 authors:Reviewed by ScreenIT
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Human airway cells prevent SARS-CoV-2 multibasic cleavage site cell culture adaptation
This article has 11 authors:This article has been curated by 1 group: -
Trans-ancestry analysis reveals genetic and nongenetic associations with COVID-19 susceptibility and severity
This article has 35 authors:Reviewed by ScreenIT
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Effect of large-scale testing platform in prevention and control of the COVID-19 pandemic: an empirical study with a novel numerical model
This article has 21 authors:Reviewed by ScreenIT
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Transferrin receptor is another receptor for SARS-CoV-2 entry
This article has 16 authors:Reviewed by ScreenIT
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The potential health and economic value of SARS-CoV-2 vaccination alongside physical distancing in the UK: a transmission model-based future scenario analysis and economic evaluation
This article has 51 authors:Reviewed by ScreenIT