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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Effects of (Un)lockdown on COVID-19 transmission: A mathematical study of different phases in India
This article has 3 authors:Reviewed by ScreenIT
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Hyperinflammatory conditions, gender differences and mortality in Indian COVID-19 patients
This article has 7 authors:Reviewed by ScreenIT
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Sequence analysis of Indian SARS-CoV-2 isolates shows a stronger interaction of mutant receptor-binding domain with ACE2
This article has 17 authors:Reviewed by ScreenIT
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Changes COVID-19 Post-Quarantine Behaviors, Hygiene and Expectations in Colombia: Population Survey from 1st to 13th September, 2020
This article has 7 authors:Reviewed by ScreenIT
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Transparency assessment of COVID-19 models
This article has 3 authors:Reviewed by ScreenIT
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Modeling fomite‐mediated SARS‐CoV‐2 exposure through personal protective equipment doffing in a hospital environment
This article has 14 authors:Reviewed by ScreenIT
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Modeling the Inactivation of Viruses from the Coronaviridae Family in Response to Temperature and Relative Humidity in Suspensions or on Surfaces
This article has 11 authors:Reviewed by ScreenIT
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Thiol drugs decrease SARS-CoV-2 lung injury in vivo and disrupt SARS-CoV-2 spike complex binding to ACE2 in vitro
This article has 21 authors:Reviewed by ScreenIT
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Modelling Decay of Population Immunity With Proposed Second Dose Deferral Strategy
This article has 1 author:Reviewed by ScreenIT
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The papain-like protease of coronaviruses cleaves ULK1 to disrupt host autophagy
This article has 7 authors:Reviewed by ScreenIT