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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Early Genomic, Epidemiological, and Clinical Description of the SARS-CoV-2 Omicron Variant in Mexico City
This article has 23 authors:Reviewed by ScreenIT
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Clinical severity of, and effectiveness of mRNA vaccines against, covid-19 from omicron, delta, and alpha SARS-CoV-2 variants in the United States: prospective observational study
This article has 59 authors:Reviewed by ScreenIT
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Limitations of Molecular and Antigen Test Performance for SARS-CoV-2 in Symptomatic and Asymptomatic COVID-19 Contacts
This article has 17 authors:Reviewed by ScreenIT
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Molecular Epidemiology of AY.28 and AY.104 Delta Sub-lineages in Sri Lanka
This article has 15 authors:Reviewed by ScreenIT
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Comparison of two T-cell assays to evaluate T-cell responses to SARS-CoV-2 following vaccination in naïve and convalescent healthcare workers
This article has 31 authors:Reviewed by ScreenIT
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Omicron BA.2 specifically evades broad sarbecovirus neutralizing antibodies
This article has 41 authors:Reviewed by ScreenIT
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Preclinical Pharmacokinetics and In Vitro Properties of GS-441524, A Potential Oral Drug Candidate for COVID-19 Treatment
This article has 11 authors:Reviewed by ScreenIT
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Vaccine protection against the SARS-CoV-2 Omicron variant in macaques
This article has 36 authors:Reviewed by ScreenIT
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An mRNA vaccine candidate for the SARS-CoV-2 Omicron variant
This article has 8 authors:Reviewed by ScreenIT
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Mechanistic Origin of Different Binding Affinities of SARS-CoV and SARS-CoV-2 Spike RBDs to Human ACE2
This article has 6 authors:Reviewed by ScreenIT