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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Depressive and anxiety symptoms and COVID-19-related factors among men and women in Nigeria
This article has 11 authors:Reviewed by ScreenIT
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An outbreak of SARS-CoV-2 with high mortality in mink (Neovison vison) on multiple Utah farms
This article has 8 authors:Reviewed by ScreenIT
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Tracing contacts to evaluate the transmission of COVID-19 from highly exposed individuals in public transportation
This article has 7 authors:Reviewed by ScreenIT
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A Chinese host genetic study discovered IFNs and causality of laboratory traits on COVID-19 severity
This article has 25 authors:Reviewed by ScreenIT
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The financial health of “swing hospitals” during the first COVID-19 outbreak
This article has 2 authors:Reviewed by ScreenIT
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Breakthrough Infection With Severe Acute Respiratory Syndrome Coronavirus 2 Among Healthcare Workers in Delhi: A Single-Institution Study
This article has 5 authors:Reviewed by ScreenIT
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Immunogenicity and In vivo protection of a variant nanoparticle vaccine that confers broad protection against emerging SARS-CoV-2 variants
This article has 21 authors:Reviewed by ScreenIT
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Cellular Activities of SARS-CoV-2 Main Protease Inhibitors Reveal Their Unique Characteristics
This article has 15 authors:Reviewed by ScreenIT
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Possible future waves of SARS-CoV-2 infection generated by variants of concern with a range of characteristics
This article has 9 authors:Reviewed by ScreenIT
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Assessing the Impact of Mask Usage on COVID-19 Transmission Using a Computer Simulation
This article has 3 authors:Reviewed by ScreenIT