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
-
Gestational SARS-CoV-2 infection is associated with placental expression of immune and trophoblast genes
This article has 23 authors:Reviewed by ScreenIT
-
Life expectancy changes since COVID-19
This article has 8 authors:Reviewed by ScreenIT
-
Bacterial metatranscriptomes in wastewater can differentiate virally infected human populations
This article has 22 authors:Reviewed by ScreenIT
-
Avoiding False-Positive SARS-CoV-2 Rapid Antigen Test Results with Point-of-Care Molecular Testing on Residual Test Buffer
This article has 8 authors:Reviewed by ScreenIT
-
Fourth Wave of COVID-19 in India : Statistical Forecasting
This article has 3 authors:Reviewed by ScreenIT
-
Unraveling the dynamics of the Omicron and Delta variants of the 2019 coronavirus in the presence of vaccination, mask usage, and antiviral treatment
This article has 4 authors:Reviewed by ScreenIT
-
Increase in SARS-CoV-2 RBD-Specific IgA and IgG Antibodies in Human Milk From Lactating Women Following the COVID-19 Booster Vaccination
This article has 1 author: -
Safety of COVID-19 vaccines in pregnancy: a Canadian National Vaccine Safety (CANVAS) network cohort study
This article has 14 authors:Reviewed by ScreenIT
-
Potent Neutralizing Activity of Polyclonal Equine Antibodies against Omicron SARS-CoV-2
This article has 7 authors:Reviewed by ScreenIT
-
Pre-clinical testing of two serologically distinct chimpanzee-origin adenovirus vectors expressing spike of SARS-CoV-2
This article has 9 authors:Reviewed by ScreenIT