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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Effectiveness of mRNA COVID-19 Vaccines among Employees in an American Healthcare System
This article has 5 authors:Reviewed by ScreenIT
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Combustible and Electronic Cigarette Exposures Increase ACE2 Activity and SARS-CoV-2 Spike Binding
This article has 11 authors:Reviewed by ScreenIT
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Tracking deaths from hitherto undetected infections can be an indicator of latent sars-cov-2 cases
This article has 3 authors:Reviewed by ScreenIT
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Drug Repurposing for the SARS‐CoV‐2 Papain‐Like Protease
This article has 8 authors:Reviewed by ScreenIT
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Group Testing Large Populations for SARS-CoV-2
This article has 6 authors:Reviewed by ScreenIT
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Clinical performance of two EUA-approved anti-COVID-19 IgG/IgM rapid lateral flow immunoassays using whole blood finger-sticks
This article has 8 authors:Reviewed by ScreenIT
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Direct comparison of venipuncture serum draws versus whole blood finger-stick specimens by anti-COVID-19 IgG/IgM rapid lateral flow immunoassay and ELISA
This article has 8 authors:Reviewed by ScreenIT
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Multisystemic Cellular Tropism of SARS-CoV-2 in Autopsies of COVID-19 Patients
This article has 16 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Healthcare use in 700 000 children and adolescents for six months after covid-19: before and after register based cohort study
This article has 7 authors:Reviewed by ScreenIT
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Antibody responses to BNT162b2 mRNA COVID-19 vaccine and their predictors among healthcare workers in a tertiary referral hospital in Japan
This article has 16 authors:Reviewed by ScreenIT