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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Comparison of the clinical characteristics and mortality in acute respiratory distress syndrome due to COVID-19 versus due to Influenza A-H1N1pdm09
This article has 4 authors:Reviewed by ScreenIT
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Comparing machine learning algorithms for predicting ICU admission and mortality in COVID-19
This article has 11 authors:Reviewed by ScreenIT
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Modelling of COVID-19 vaccination strategies and herd immunity, in scenarios of limited and full vaccine supply in NSW, Australia
This article has 3 authors:Reviewed by ScreenIT
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Understanding the phase separation characteristics of nucleocapsid protein provides a new therapeutic opportunity against SARS-CoV-2
This article has 20 authors:Reviewed by ScreenIT
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Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset
This article has 2 authors:This article has been curated by 1 group: -
COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown
This article has 7 authors:Reviewed by ScreenIT
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Excess mortality among Latino people in California during the COVID-19 pandemic
This article has 7 authors:Reviewed by ScreenIT
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Social determinants of COVID-19 mortality at the county level
This article has 3 authors:Reviewed by ScreenIT
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A method for detection of SARS-CoV-2 RNA in healthy human stool: a validation study
This article has 16 authors:Reviewed by ScreenIT
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Persistence of Anti-SARS-CoV-2 Antibodies in Non-Hospitalized COVID-19 Convalescent Health Care Workers
This article has 20 authors:Reviewed by ScreenIT