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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Household Transmission of SARS-CoV-2
This article has 5 authors: -
A fractal kinetics SI model can explain the dynamics of COVID-19 epidemics
This article has 2 authors:Reviewed by ScreenIT
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Anti-CoVid19 plasmid DNA vaccine induces a potent immune response in rodents by Pyro-drive Jet Injector intradermal inoculation
This article has 14 authors:Reviewed by ScreenIT
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SARS-CoV-2 infection causes transient olfactory dysfunction in mice
This article has 18 authors:Reviewed by ScreenIT
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Zorro versus Covid-19: fighting the pandemic with face masks
This article has 1 author:Reviewed by ScreenIT
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Accounting for body mass effects in the estimation of field metabolic rates from body acceleration
This article has 7 authors:Reviewed by ScreenIT
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Sixteen novel lineages of SARS-CoV-2 in South Africa
This article has 31 authors:Reviewed by ScreenIT
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Genetic epidemiology of variants associated with immune escape from global SARS-CoV-2 genomes
This article has 15 authors:Reviewed by ScreenIT
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Addressing a complicated problem: can COVID-19 asymptomatic cases be detected – and epidemics stopped− when testing is limited and the location of such cases unknown?
This article has 5 authors:Reviewed by ScreenIT
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IL-6 and IL-10 as predictors of disease severity in COVID-19 patients: results from meta-analysis and regression
This article has 5 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT