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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Concentration of the cellular material in the nasopharyngeal swabs increases the clinical sensitivity of SARS-CoV2 RT-PCR
This article has 3 authors:Reviewed by ScreenIT
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A Simple Covid-19 Epidemic Model and Containment Policy in France
This article has 1 author:Reviewed by ScreenIT
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An orally bioavailable SARS-CoV-2 main protease inhibitor exhibits improved affinity and reduced sensitivity to mutations
This article has 22 authors:Reviewed by ScreenIT
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Analysis of the SARS-Cov-2 epidemic in Lombardy (Italy) in its early phase. Are we going in the right direction?
This article has 1 author:Reviewed by ScreenIT
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Clinical characteristics and antibody response to SARS-CoV-2 spike 1 protein using VITROS Anti-SARS-CoV-2 antibody tests in COVID-19 patients in Japan
This article has 11 authors:Reviewed by ScreenIT
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Genomic Epidemiology of SARS-CoV-2 in Guangdong Province, China
This article has 41 authors:Reviewed by ScreenIT
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The effect of eviction moratoria on the transmission of SARS-CoV-2
This article has 15 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Impact of COVID-19 on migrants’ access to primary care and implications for vaccine roll-out: a national qualitative study
This article has 7 authors:Reviewed by ScreenIT
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‘Dark matter’, second waves and epidemiological modelling
This article has 3 authors:Reviewed by ScreenIT
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Clinical characteristics of children with COVID-19 admitted in a tertiary referral center in Perú
This article has 11 authors:Reviewed by ScreenIT