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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Accelerating manufacturing to enable large-scale supply of a new adenovirus-vectored vaccine within 100 days
This article has 12 authors:Reviewed by ScreenIT
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A systematic review of observational methods used to quantify personal protective behaviours among members of the public during the COVID-19 pandemic, and the concordance between observational and self-report measures in infectious disease health protection
This article has 5 authors:Reviewed by ScreenIT
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Allosteric Determinants of the SARS-CoV-2 Spike Protein Binding with Nanobodies: Examining Mechanisms of Mutational Escape and Sensitivity of the Omicron Variant
This article has 1 author:Reviewed by ScreenIT
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Minimal observed impact of HLA genotype on hospitalization and severity of SARS‐CoV ‐2 infection
This article has 5 authors:Reviewed by ScreenIT
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Construction of a potent pan-vaccine based on the evolutionary tendency of SARS-CoV-2 spike protein
This article has 24 authors:Reviewed by ScreenIT
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Nucleocapsid 203 mutations enhance SARS-CoV-2 immune evasion
This article has 14 authors:Reviewed by ScreenIT
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Efficacy of antiviral drugs against the omicron variant of SARS-CoV-2
This article has 9 authors:Reviewed by ScreenIT
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Structural basis for antibody resistance to SARS-CoV-2 omicron variant
This article has 11 authors:Reviewed by ScreenIT
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Anti-SARS-CoV-2 human antibodies retaining neutralizing activity against SARS-CoV-2 B.1.1.529 (omicron)
This article has 15 authors:Reviewed by ScreenIT
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Sputnik Light booster after Sputnik V vaccination induces robust neutralizing antibody response to B.1.1.529 (Omicron) SARS-CoV-2 variant
This article has 20 authors:Reviewed by ScreenIT