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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Epidemiology study of SARS-CoV-2 pandemic in India, the first and second wave
This article has 4 authors:Reviewed by ScreenIT
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Government messaging about COVID-19 vaccination in Canada and Australia: a Narrative Policy Framework study
This article has 2 authors:Reviewed by ScreenIT
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Fluvoxamine for Outpatient COVID-19 to Prevent Hospitalization: A Systematic Review and Meta-Analysis
This article has 8 authors:Reviewed by ScreenIT
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ACE2-independent SARS-CoV-2 infection and mouse adaption emerge after passage in cells expressing human and mouse ACE2
This article has 7 authors:Reviewed by ScreenIT
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A highly sensitive cell-based luciferase assay for high-throughput automated screening of SARS-CoV-2 nsp5/3CLpro inhibitors
This article has 17 authors:Reviewed by ScreenIT
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Unraveling the antiviral activity of plitidepsin against SARS-CoV-2 by subcellular and morphological analysis
This article has 16 authors:Reviewed by ScreenIT
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Analysis of SARS-CoV-2 synonymous codon usage evolution throughout the COVID-19 pandemic
This article has 3 authors:Reviewed by ScreenIT
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Vandetanib Reduces Inflammatory Cytokines and Ameliorates COVID-19 in Infected Mice
This article has 22 authors:Reviewed by ScreenIT
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Neutralization and Stability of SARS-CoV-2 Omicron Variant
This article has 16 authors:Reviewed by ScreenIT
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Single Amino Acid Change Mutation in the Hydrophobic Core of the N-terminal Domain of P22 TSP affects the Proteins Stability
This article has 2 authors:Reviewed by ScreenIT