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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SARS-CoV-2 vaccination intentions among mothers of children aged 9 to 12 years: a survey of the All Our Families cohort
This article has 7 authors:Reviewed by ScreenIT
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Molecular Dynamics Analysis of a Flexible Loop at the Binding Interface of the SARS-CoV-2 Spike Protein Receptor-Binding Domain
This article has 6 authors:Reviewed by ScreenIT
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Interplay of Monocytes and T Lymphocytes in COVID-19 Severity
This article has 9 authors:Reviewed by ScreenIT
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Detection of the novel SARS-CoV-2 European lineage B.1.177 in Ontario, Canada
This article has 15 authors:Reviewed by ScreenIT
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COVID 19 healthcare facility demand forecasts for rural residents
This article has 1 author:Reviewed by ScreenIT
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Mental health service activity during COVID-19 lockdown: South London and Maudsley data on working age community and home treatment team services and mortality from February to mid-May 2020
This article has 3 authors:Reviewed by ScreenIT
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Differing impacts of global and regional responses on SARS-CoV-2 transmission cluster dynamics
This article has 9 authors:Reviewed by ScreenIT
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Low Seroprevalence of SARS-CoV-2 in Rhode Island blood donors during may 2020 as determined using multiple serological assay formats
This article has 13 authors:Reviewed by ScreenIT
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The Prognostic Value of Eosinophil Recovery in COVID-19: A Multicentre, Retrospective Cohort Study on Patients Hospitalised in Spanish Hospitals
This article has 26 authors:Reviewed by ScreenIT
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Impulse dispersion of aerosols during playing wind instruments
This article has 11 authors:Reviewed by ScreenIT