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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Population vulnerability to COVID-19 in Europe: a burden of disease analysis
This article has 20 authors:Reviewed by ScreenIT
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AKI during COVID-19 infection: low incidence, high risk of death
This article has 2 authors:Reviewed by ScreenIT
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Enzyme immunoassay for SARS-CoV-2 antibodies in dried blood spot samples: A minimally-invasive approach to facilitate community- and population-based screening
This article has 10 authors:Reviewed by ScreenIT
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Predicted impact of the COVID-19 pandemic on global tuberculosis deaths in 2020
This article has 1 author:Reviewed by ScreenIT
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Balancing revenue generation with capacity generation: case distribution, financial impact and hospital capacity changes from cancelling or resuming elective surgeries in the US during COVID-19
This article has 10 authors:Reviewed by ScreenIT
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A Cohort of Patients with COVID-19 in a Major Teaching Hospital in Europe
This article has 30 authors:Reviewed by ScreenIT
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Development and validation of direct RT-LAMP for SARS-CoV-2
This article has 13 authors:Reviewed by ScreenIT
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Structure of anxiety associated with СOVID-19 pandemic: the online survey results
This article has 7 authors:Reviewed by ScreenIT
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Cohort profile: a national, community-based prospective cohort study of SARS-CoV-2 pandemic outcomes in the USA—the CHASING COVID Cohort study
This article has 15 authors:Reviewed by ScreenIT
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A simulation-based procedure to estimate base rates from Covid-19 antibody test results I: Deterministic test reliabilities
This article has 2 authors:Reviewed by ScreenIT