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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Immunogenicity and safety of a recombinant adenovirus type-5 COVID-19 vaccine in adults: Data from a randomised, double-blind, placebo-controlled, single-dose, phase 3 trial in Russia
This article has 15 authors:Reviewed by ScreenIT
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Trajectories of gene expression, seasonal influenza, and within-host seasonal immunity: transfer value to covid-19
This article has 6 authors:Reviewed by ScreenIT
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Thiopurines inhibit coronavirus Spike protein processing and incorporation into progeny virions
This article has 16 authors:Reviewed by ScreenIT
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Crystal structures and fragment screening of SARS-CoV-2 NSP14 reveal details of exoribonuclease activation and mRNA capping and provide starting points for antiviral drug development
This article has 3 authors:Reviewed by ScreenIT
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Dissecting the role of the human microbiome in COVID-19 via metagenome-assembled genomes
This article has 3 authors:Reviewed by ScreenIT
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High-throughput molecular dynamics-based alchemical free energy calculations for predicting the binding free energy change associated with the common mutations in the spike receptor-binding domain of SARS-CoV-2
This article has 2 authors:Reviewed by ScreenIT
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Impact of SARS-CoV-2 vaccination of children ages 5–11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021–March 2022: a multi-model study
This article has 63 authors:Reviewed by ScreenIT
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Community engagement to support COVID-19 vaccine uptake: a living systematic review protocol
This article has 9 authors:Reviewed by ScreenIT
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Trends, variation and clinical characteristics of recipients of antivirals and neutralising monoclonal antibodies for non-hospitalised COVID-19: a descriptive cohort study of 23.4 million people in OpenSAFELY
This article has 41 authors:Reviewed by ScreenIT
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DISCERN: deep single-cell expression reconstruction for improved cell clustering and cell subtype and state detection
This article has 9 authors:Reviewed by ScreenIT