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
-
COVID-19 mortality rate in Russia: forecasts and reality evaluation
This article has 2 authors:Reviewed by ScreenIT
-
Population Changes in Seroprevalence among a Statewide Sample in the United States
This article has 12 authors:Reviewed by ScreenIT
-
Now casting and Forecasting of COVID-19 outbreak in the National Capital Region of Delhi
This article has 6 authors:Reviewed by ScreenIT
-
A comparative evaluation of a dye-based and probe-based RT-qPCR assay for the screening of SARS-CoV-2 using individual and pooled-sample testing
This article has 15 authors:Reviewed by ScreenIT
-
A model for pH coupling of the SARS-CoV-2 spike protein open/closed equilibrium
This article has 1 author:Reviewed by ScreenIT
-
CD8 T cell epitope generation toward the continually mutating SARS-CoV-2 spike protein in genetically diverse human population: Implications for disease control and prevention
This article has 2 authors:Reviewed by ScreenIT
-
Performance of SARS-CoV-2 serology tests: Are they good enough?
This article has 6 authors:Reviewed by ScreenIT
-
Practical strategies for SARS-CoV-2 RT-PCR testing in resource-constrained settings
This article has 10 authors:Reviewed by ScreenIT
-
Clade GR and clade GH isolates of SARS-CoV-2 in Asia show highest amount of SNPs
This article has 3 authors:Reviewed by ScreenIT
-
Impact of Coronavirus Disease-2019 Pandemic on Hemodialysis Care Delivery Pattern in Karnataka, India
This article has 6 authors:Reviewed by ScreenIT