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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SARS-CoV-2 viral load is associated with increased disease severity and mortality
This article has 131 authors:Reviewed by ScreenIT
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COVID-19 Higher Mortality in Chinese Regions With Chronic Exposure to Lower Air Quality
This article has 2 authors:Reviewed by ScreenIT
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Therapeutic Targeting of Transcription Factors to Control the Cytokine Release Syndrome in COVID-19
This article has 6 authors:Reviewed by ScreenIT
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Modelling the epidemic trend of the 2019-nCOV outbreak in Hubei Province, China
This article has 1 author:Reviewed by ScreenIT
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Immunogenicity of novel mRNA COVID-19 vaccine MRT5500 in mice and non-human primates
This article has 27 authors:Reviewed by ScreenIT
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Structural characterization of cocktail-like targeting polysaccharides from Ecklonia kurome Okam and their anti-SARS-CoV-2 activities invitro
This article has 16 authors:Reviewed by ScreenIT
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New-onset IgG autoantibodies in hospitalized patients with COVID-19
This article has 49 authors:Reviewed by ScreenIT
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Tool for Estimating the Probability of Having COVID-19 With 1 or More Negative RT-PCR Results
This article has 3 authors:Reviewed by ScreenIT
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Intrinsic signal amplification by type III CRISPR-Cas systems provides a sequence-specific SARS-CoV-2 diagnostic
This article has 15 authors:Reviewed by ScreenIT
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Sensitive quantitative detection of SARS-CoV-2 in clinical samples using digital warm-start CRISPR assay
This article has 5 authors:Reviewed by ScreenIT