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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The prevalence of adaptive immunity to COVID-19 and reinfection after recovery – a comprehensive systematic review and meta-analysis
This article has 16 authors:Reviewed by ScreenIT
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Combining antibody markers for serosurveillance of SARS-CoV-2 to estimate seroprevalence and time-since-infection
This article has 8 authors:Reviewed by ScreenIT
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An adjuvanted SARS-CoV-2 RBD nanoparticle elicits neutralizing antibodies and fully protective immunity in aged mice
This article has 32 authors:Reviewed by ScreenIT
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Age-related differences in immune dynamics during SARS-CoV-2 infection in rhesus macaques
This article has 23 authors:Reviewed by ScreenIT
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Landscape of SARS-CoV-2 genomic surveillance, public availability extent of genomic data, and epidemic shaped by variants: a global descriptive study
This article has 15 authors:Reviewed by ScreenIT
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Targeted isolation of diverse human protective broadly neutralizing antibodies against SARS-like viruses
This article has 29 authors:Reviewed by ScreenIT
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Digital spatial profiling of collapsing glomerulopathy
This article has 6 authors:Reviewed by ScreenIT
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Metabolic and Immune Markers for Precise Monitoring of COVID-19 Severity and Treatment
This article has 10 authors:Reviewed by ScreenIT
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Previous COVID-19 Infection and Antibody Levels After Vaccination
This article has 21 authors:Reviewed by ScreenIT
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Artemisia annua L. hot-water extracts show potent activity in vitro against Covid-19 variants including delta
This article has 5 authors:Reviewed by ScreenIT