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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COVID-19 Hospitalization Among Children <18 Years by Variant Wave in Norway
This article has 6 authors:Reviewed by ScreenIT
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Labor market participation and depression during the COVID-19 epidemic among young adults (18 to 30 years): a nationally representative study in France
This article has 11 authors:Reviewed by ScreenIT
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Impact of the Russian invasion of Ukraine on the COVID-19 pandemic dynamics
This article has 1 author:Reviewed by ScreenIT
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Repeated ethanol exposure and withdrawal alters angiotensin‐converting enzyme 2 expression in discrete brain regions: Implications for SARS‐CoV ‐2 neuroinvasion
This article has 5 authors:Reviewed by ScreenIT
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Primary exposure to SARS-CoV-2 variants elicits convergent epitope specificities, immunoglobulin V gene usage and public B cell clones
This article has 56 authors:Reviewed by ScreenIT
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Subcellular mapping of the protein landscape of SARS-CoV-2 infected cells for target-centric drug repurposing
This article has 18 authors:Reviewed by ScreenIT
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A mosaic-type trimeric RBD-based COVID-19 vaccine candidate induces potent neutralization against Omicron and other SARS-CoV-2 variants
This article has 25 authors:This article has been curated by 1 group: -
Discovery of a druggable copper-signaling pathway that drives cell plasticity and inflammation
This article has 25 authors:Reviewed by ScreenIT
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Neutralization of Omicron BA.1, BA.2, and BA.3 SARS-CoV-2 by 3 doses of BNT162b2 vaccine
This article has 12 authors:Reviewed by ScreenIT
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Titers of antibodies the receptor-binding domain (RBD) of ancestral SARS-CoV-2 are predictive for levels of neutralizing antibodies to multiple variants
This article has 39 authors:Reviewed by ScreenIT