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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Analysis of SARS-CoV-2 spike glycosylation reveals shedding of a vaccine candidate
This article has 11 authors:Reviewed by ScreenIT
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COVID-19 optimal vaccination policies: A modeling study on efficacy, natural and vaccine-induced immunity responses
This article has 4 authors:Reviewed by ScreenIT
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Hydroxychloroquine Increased Anxiety-Like Behaviors and Disrupted the Expression of Some Related Genes in the Mouse Brain
This article has 4 authors: -
Emergence of universality in the transmission dynamics of COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Pre-existing cardiovascular disease rather than cardiovascular risk factors drives mortality in COVID-19
This article has 9 authors:Reviewed by ScreenIT
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Epidemiological Profile and Transmission Dynamics of COVID-19 in the Philippines
This article has 4 authors:Reviewed by ScreenIT
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Occurrence of Cardiovascular Complications Associated with SARS-CoV-2 Infection: A Systematic Review
This article has 9 authors:Reviewed by ScreenIT
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Predicting Hospital Utilization and Inpatient Mortality of Patients Tested for COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Estimation of fatality rate in Africa through the behavior of COVID-19 in Italy relevance to age profiles
This article has 8 authors:Reviewed by ScreenIT
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Estimating missing deaths in Delhi’s COVID-19 data
This article has 1 author:Reviewed by ScreenIT