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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Production of trimeric SARS‐CoV‐2 spike protein by CHO cells for serological COVID‐19 testing
This article has 16 authors:Reviewed by ScreenIT
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Implications of the COVID-19 pandemic in eliminating trachoma as a public health problem
This article has 11 authors:Reviewed by ScreenIT
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SARS‐CoV‐2 infections amongst personnel providing home care services for older persons in Stockholm, Sweden
This article has 14 authors:Reviewed by ScreenIT
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A versatile web app for identifying the drivers of COVID-19 epidemics
This article has 4 authors:Reviewed by ScreenIT
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Epidemiology of Reopening in the COVID-19 Pandemic in the United States, Europe and Asia
This article has 5 authors:Reviewed by ScreenIT
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Race, socioeconomic deprivation, and hospitalization for COVID-19 in English participants of a national biobank
This article has 5 authors:Reviewed by ScreenIT
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Evidence of antigenic imprinting in sequential Sarbecovirus immunization
This article has 11 authors:Reviewed by ScreenIT
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Comparisons of COVID-19 dynamics in the different countries of the World using Time-Series clustering
This article has 3 authors:Reviewed by ScreenIT
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OxCOVID19 Database, a multimodal data repository for better understanding the global impact of COVID-19
This article has 13 authors:Reviewed by ScreenIT
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Potency and timing of antiviral therapy as determinants of duration of SARS-CoV-2 shedding and intensity of inflammatory response
This article has 3 authors:Reviewed by ScreenIT