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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Antibody attributes that predict the neutralization and effector function of polyclonal responses to SARS-CoV-2
This article has 21 authors:Reviewed by ScreenIT
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Full vaccination against COVID-19 suppresses SARS-CoV-2 delta variant and spike gene mutation frequencies and generates purifying selection pressure
This article has 2 authors:Reviewed by ScreenIT
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Mental health and social isolation under repeated mild lockdowns in Japan
This article has 8 authors:Reviewed by ScreenIT
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Rapid, robust, and sustainable antibody responses to mRNA COVID-19 vaccine in convalescent COVID-19 individuals
This article has 16 authors:Reviewed by ScreenIT
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Characterising COVID-19 empirical research production in Latin America and the Caribbean: A scoping review
This article has 11 authors:Reviewed by ScreenIT
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The impact of vaccination strategies for COVID-19 in the context of emerging variants and increasing social mixing in Bogotá, Colombia: a mathematical modelling study
This article has 6 authors:Reviewed by ScreenIT
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GlycoSHIELD: a versatile pipeline to assess glycan impact on protein structures
This article has 6 authors:Reviewed by ScreenIT
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Strategies to Estimate Prevalence of SARS-CoV-2 Antibodies in a Texas Vulnerable Population: Results From Phase I of the Texas Coronavirus Antibody Response Survey
This article has 15 authors:Reviewed by ScreenIT
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Bacterial coinfections in COVID: Prevalence, antibiotic sensitivity patterns and clinical outcomes from a tertiary institute of Northern India
This article has 7 authors:Reviewed by ScreenIT
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COVID-19 mortality prediction model, 3C-M, built for use in resource limited settings - understanding the relevance of neutrophilic leukocytosis in predicting disease severity and mortality
This article has 6 authors:Reviewed by ScreenIT