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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Synthetic protein antigens for COVID-19 diagnostics
This article has 8 authors:Reviewed by ScreenIT
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Analytical and clinical performances of a SARS-CoV-2 S-RBD IgG assay: comparison with neutralization titers
This article has 12 authors:Reviewed by ScreenIT
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Identification of SARS-CoV-2–induced pathways reveals drug repurposing strategies
This article has 16 authors:Reviewed by ScreenIT
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Characterization of the NiRAN domain from RNA-dependent RNA polymerase provides insights into a potential therapeutic target against SARS-CoV-2
This article has 13 authors:Reviewed by ScreenIT
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Combinatorial Approach with Mass Spectrometry and Lectin Microarray Dissected Site-Specific Glycostem and Glycoleaf Features of the Virion-Derived Spike Protein of Ancestral and γ Variant SARS-CoV-2 Strains
This article has 8 authors:Reviewed by ScreenIT
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Flexibility and mobility of SARS-CoV-2-related protein structures
This article has 3 authors:Reviewed by ScreenIT
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Longitudinal changes in physical activity during and after the first national lockdown due to the COVID-19 pandemic in England
This article has 5 authors:Reviewed by ScreenIT
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Rapid evolution of SARS-CoV-2 challenges human defenses
This article has 9 authors:Reviewed by ScreenIT
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Integrated immunovirological profiling validates plasma SARS-CoV-2 RNA as an early predictor of COVID-19 mortality
This article has 43 authors:Reviewed by ScreenIT
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Use of Modeling to Inform Decision Making in North Carolina during the COVID-19 Pandemic: A Qualitative Study
This article has 9 authors:Reviewed by ScreenIT