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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A randomized, double-blind phase I clinical trial of two recombinant dimeric RBD COVID-19 vaccine candidates: Safety, reactogenicity and immunogenicity
This article has 28 authors:Reviewed by ScreenIT
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Structure-selected RBM immunogens prime polyclonal memory responses that neutralize SARS-CoV-2 variants of concern
This article has 13 authors:Reviewed by ScreenIT
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A high throughput screening assay for inhibitors of SARS-CoV-2 pseudotyped particle entry
This article has 16 authors:Reviewed by ScreenIT
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Frequency of surveillance testing necessary to reduce transmission of the Delta variant of SARS-CoV-2
This article has 2 authors:Reviewed by ScreenIT
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Unique Peptide Signatures Of SARS-CoV-2 Against Human Proteome Reveal Variants’ Immune Escape And Infectiveness
This article has 4 authors:Reviewed by ScreenIT
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COVID-19 data reporting systems in Africa reveal insights for future pandemics
This article has 8 authors:Reviewed by ScreenIT
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Why a Globally Fair COVID-19 Vaccination? An Analysis based on Agent-Based Simulation
This article has 1 author:Reviewed by ScreenIT
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Dynamic allostery highlights the evolutionary differences between the CoV-1 and CoV-2 main proteases
This article has 3 authors:Reviewed by ScreenIT
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Hierarchical Gaussian Processes and Mixtures of Experts to Model COVID-19 Patient Trajectories
This article has 5 authors:Reviewed by ScreenIT
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Genetic association of TMPRSS2 rs2070788 polymorphism with COVID-19 case fatality rate among Indian populations
This article has 4 authors:Reviewed by ScreenIT