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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Mutations in SARS-CoV-2 are on the increase against the acquired immunity
This article has 1 author:Reviewed by ScreenIT
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Neutralizing SARS-CoV-2 Spike Antibodies against Omicron in Paired Samples after Two or Three Doses of mRNA Vaccine
This article has 9 authors:Reviewed by ScreenIT
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Distinct genetic determinants and mechanisms of SARS-CoV-2 resistance to remdesivir
This article has 17 authors:Reviewed by ScreenIT
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Susceptibility of Wild Canids to SARS-CoV-2
This article has 5 authors:Reviewed by ScreenIT
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Estimating COVID-19 Vaccination and Booster Effectiveness Using Electronic Health Records From an Academic Medical Center in Michigan
This article has 5 authors:Reviewed by ScreenIT
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Polygenic predisposition to venous thromboembolism is associated with increased COVID-19 positive testing rates
This article has 49 authors:Reviewed by ScreenIT
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Virucidal activity and mechanism of action of cetylpyridinium chloride against SARS-CoV-2
This article has 4 authors:Reviewed by ScreenIT
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Populist Attitude and Conspiracist beliefs contribution to the overconfidence about the risk of Covid-19: implications for Preventive Health Behaviors
This article has 2 authors:Reviewed by ScreenIT
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Visible blue light inactivates SARS-CoV-2 variants and inhibits Delta replication in differentiated human airway epithelia
This article has 11 authors:Reviewed by ScreenIT
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Combating the SARS-CoV-2 Omicron variant with non-Omicron neutralizing antibodies
This article has 16 authors:Reviewed by ScreenIT