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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Adenovirus type 5 SARS-CoV-2 vaccines delivered orally or intranasally reduced disease severity and transmission in a hamster model
This article has 11 authors:Reviewed by ScreenIT
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TREM2+ and interstitial macrophages orchestrate airway inflammation in SARS-CoV-2 infection in rhesus macaques
This article has 27 authors:Reviewed by ScreenIT
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Diversity of SARS-CoV-2 genome among various strains identified in Lucknow, Uttar Pradesh
This article has 5 authors:Reviewed by ScreenIT
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COVID-19 aerosol transmission simulation-based risk analysis for in-person learning
This article has 5 authors:Reviewed by ScreenIT
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Mitigating the SARS-CoV-2 Delta disease burden in Australia by non-pharmaceutical interventions and vaccinating children: a modelling analysis
This article has 3 authors:Reviewed by ScreenIT
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Longitudinal characterization of circulating neutrophils uncovers phenotypes associated with severity in hospitalized COVID-19 patients
This article has 32 authors:Reviewed by ScreenIT
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COVID-19 Vaccine: Newspaper Coverage of the side effects of the vaccine in Nigeria
This article has 3 authors:Reviewed by ScreenIT
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Characterization and Structural Prediction of ORF10, ORF7b, ORF7a, ORF6, Membrane Glycoprotein, and Envelope Protein in SARS-CoV-2 Bangladeshi Variant through Bioinformatics Approach
This article has 3 authors:Reviewed by ScreenIT
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De Novo-Whole Genome Assembly of the Roborovski Dwarf Hamster ( Phodopus roborovskii ) Genome: An Animal Model for Severe/Critical COVID-19
This article has 10 authors:Reviewed by ScreenIT
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In vitro activity of cysteamine against SARS-CoV-2 variants
This article has 7 authors:Reviewed by ScreenIT