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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Modelling suggests limited change in the reproduction number from reopening Norwegian kindergartens and schools during the COVID-19 pandemic
This article has 7 authors:Reviewed by ScreenIT
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Further Evidence of a Possible Correlation between the Severity of Covid-19 and BCG Immunization
This article has 1 author:Reviewed by ScreenIT
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Investigating duration and intensity of Covid-19 social-distancing strategies
This article has 3 authors:Reviewed by ScreenIT
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Dysregulated naive B cells and de novo autoreactivity in severe COVID-19
This article has 30 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Effect of mutations in the SARS-CoV-2 spike protein on protein stability, cleavage, and cell-cell fusion function
This article has 10 authors:Reviewed by ScreenIT
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Risk of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Transmission Among Air Passengers in China
This article has 16 authors:Reviewed by ScreenIT
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Estimating the ascertainment rate of SARS-CoV-2 infection in Wuhan, China: implications for management of the global outbreak
This article has 3 authors:Reviewed by ScreenIT
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Hindsight is 2020 vision: a characterisation of the global response to the COVID-19 pandemic
This article has 6 authors:Reviewed by ScreenIT
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Modelling SARS-CoV-2 transmission in a UK university setting
This article has 5 authors:Reviewed by ScreenIT
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Detections and SIR simulations of the COVID-19 pandemic waves in Ukraine
This article has 1 author:Reviewed by ScreenIT