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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Initial SARS-CoV-2 vaccination response can predict booster response for BNT162b2 but not for AZD1222
This article has 10 authors:Reviewed by ScreenIT
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Following the science? Views from scientists on government advisory boards during the COVID-19 pandemic: a qualitative interview study in five European countries
This article has 5 authors:Reviewed by ScreenIT
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The Lived Experience of Implementing Infection Control Measures in Care Homes during two waves of the COVID-19 Pandemic. A mixed-methods study
This article has 5 authors:Reviewed by ScreenIT
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Immunogenicity of Oxford-AstraZeneca COVID-19 Vaccine in Vietnamese Health-Care Workers
This article has 24 authors:Reviewed by ScreenIT
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Simplified Point-of-Care Full SARS-CoV-2 Genome Sequencing Using Nanopore Technology
This article has 6 authors:Reviewed by ScreenIT
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Insights into the mutation T1117I in the spike and the lineage B.1.1.389 of SARS-CoV-2 circulating in Costa Rica
This article has 1 author:Reviewed by ScreenIT
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Deaths in children and young people in England after SARS-CoV-2 infection during the first pandemic year
This article has 15 authors:Reviewed by ScreenIT
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Elucidating Post-COVID-19 manifestations in India
This article has 5 authors:Reviewed by ScreenIT
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Symptomatic, Presymptomatic, and Asymptomatic Transmission of SARS-CoV-2 in a University Student Population, August–November 2020
This article has 5 authors:Reviewed by ScreenIT
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On the effectiveness of COVID-19 restrictions and lockdowns: Pan metron ariston
This article has 1 author:Reviewed by ScreenIT