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 statistical forecast of LOW mortality (< 400,000 deaths) due to COVID-19, for the whole WORLD
This article has 1 author:Reviewed by ScreenIT
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COVID-19 in people living with human immunodeficiency virus: a case series of 33 patients
This article has 14 authors:Reviewed by ScreenIT
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Novel multiple swab method enables high efficiency in SARS‐CoV ‐2 screenings without loss of sensitivity for screening of a complete population
This article has 7 authors:Reviewed by ScreenIT
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Adoption of Digital Technologies in Health Care During the COVID-19 Pandemic: Systematic Review of Early Scientific Literature
This article has 6 authors:Reviewed by ScreenIT
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Modeling serological testing to inform relaxation of social distancing for COVID-19 control
This article has 6 authors:Reviewed by ScreenIT
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Racial, Economic, and Health Inequality and COVID-19 Infection in the United States
This article has 8 authors:Reviewed by ScreenIT
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Performance & Quality Evaluation of Marketed COVID-19 RNA Detection Kits
This article has 6 authors:Reviewed by ScreenIT
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COVID-19 and Inflammatory Bowel Diseases: Risk Assessment, Shared Molecular Pathways, and Therapeutic Challenges
This article has 5 authors:Reviewed by ScreenIT
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Comparative Transcriptome Analysis Reveals the Intensive Early Stage Responses of Host Cells to SARS-CoV-2 Infection
This article has 13 authors:Reviewed by ScreenIT
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Protoporphyrin IX and verteporfin prevent SARS-CoV-2 infection in vitro and in a mouse model expressing human ACE2
This article has 17 authors:Reviewed by ScreenIT