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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A study on the relationship between Bacillus CalmetteGurin (BCG) vaccination and Covid-19 prevalence: Do other confounders warrant investigation?
This article has 2 authors:Reviewed by ScreenIT
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The ongoing COVID-19 epidemic in Minas Gerais, Brazil: insights from epidemiological data and SARS-CoV-2 whole genome sequencing
This article has 27 authors:Reviewed by ScreenIT
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Liver histopathology in severe COVID 19 respiratory failure is suggestive of vascular alterations
This article has 13 authors:Reviewed by ScreenIT
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Studying the pathophysiology of coronavirus disease 2019: a protocol for the Berlin prospective COVID-19 patient cohort (Pa-COVID-19)
This article has 43 authors:Reviewed by ScreenIT
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Spread of Covid-19 in the United States is controlled
This article has 7 authors:Reviewed by ScreenIT
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Health and Demographic Impact on COVID-19 Infection and Mortality in US Counties
This article has 2 authors:Reviewed by ScreenIT
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Screening of SARS-CoV-2 among homeless people, asylum-seekers and other people living in precarious conditions in Marseille, France, March–April 2020
This article has 17 authors:Reviewed by ScreenIT
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Multi-ancestry Mendelian randomization of omics traits revealing drug targets of COVID-19 severity
This article has 18 authors:Reviewed by ScreenIT
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Selection of homemade mask materials for preventing transmission of COVID-19: A laboratory study
This article has 14 authors:Reviewed by ScreenIT
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Clinical performance of SARS-CoV-2 IgG antibody tests and potential protective immunity
This article has 5 authors:Reviewed by ScreenIT