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
-
Heart Block in the Patients with COVID-19
This article has 6 authors:Reviewed by ScreenIT
-
An elite broadly neutralizing antibody protects SARS-CoV-2 Omicron variant challenge
This article has 21 authors:Reviewed by ScreenIT
-
Cognitive function following SARS-CoV-2 infection in a population-representative Canadian sample
This article has 8 authors:Reviewed by ScreenIT
-
Radiological follow-up of adults hospitalised with pneumonia and SARS-CoV-2 infection, in Bristol UK, during the COVID19 pandemic
This article has 4 authors:Reviewed by ScreenIT
-
Daily Lactobacillus Probiotic versus Placebo in COVID-19-Exposed Household Contacts (PROTECT-EHC): A Randomized Clinical Trial
This article has 21 authors:Reviewed by ScreenIT
-
COVID-19 vaccination status is associated with physical activity in German-speaking countries: the COR-PHYS-Q cohort study
This article has 6 authors:Reviewed by ScreenIT
-
The French Covid-19 vaccination policy did not solve vaccination inequities: a nationwide study on 64.5 million people
This article has 5 authors:Reviewed by ScreenIT
-
Association of SARS-CoV-2 Seropositivity and Symptomatic Reinfection in Children in Nicaragua
This article has 19 authors:Reviewed by ScreenIT
-
Discordant SARS-CoV-2 PCR and Rapid Antigen Test Results When Infectious: A December 2021 Occupational Case Series
This article has 4 authors:Reviewed by ScreenIT
-
Test to release from isolation after testing positive for SARS-CoV-2
This article has 3 authors:Reviewed by ScreenIT