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
-
Sex‐associated differences between BMI and SARS‐CoV‐2 antibody titers following the BNT162b2 vaccine
This article has 11 authors:Reviewed by ScreenIT
-
RBD Double Mutations of SARS-CoV-2 Strains Increase Transmissibility through Enhanced Interaction between RBD and ACE2 Receptor
This article has 3 authors:Reviewed by ScreenIT
-
Highlighting the impact of social relationships on the propagation of respiratory viruses using percolation theory
This article has 3 authors:Reviewed by ScreenIT
-
COVID-19 scenarios for comparing the effectiveness of age-specific vaccination regimes, exemplified for the city of Aschaffenburg (Germany)
This article has 3 authors:Reviewed by ScreenIT
-
SARS-CoV-2 Variant Tracking and Mitigation During In-Person Learning at a Midwestern University in the 2020-2021 School Year
This article has 8 authors:Reviewed by ScreenIT
-
Spatial inequity in distribution of COVID-19 vaccination services in Aotearoa
This article has 4 authors:Reviewed by ScreenIT
-
Protection of BNT162b2 Vaccine Booster against Covid-19 in Israel
This article has 11 authors:Reviewed by ScreenIT
-
Genomic Epidemiology of Early SARS-CoV-2 Transmission Dynamics, Gujarat, India
This article has 13 authors:Reviewed by ScreenIT
-
The impact of pausing the Oxford-AstraZeneca COVID-19 vaccine on uptake in Europe: a difference-in-differences analysis
This article has 2 authors:Reviewed by ScreenIT
-
Total infectome characterization of respiratory infections in pre-COVID-19 Wuhan, China
This article has 17 authors:Reviewed by ScreenIT