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
-
Age-Related Susceptibility of Ferrets to SARS-CoV-2 Infection
This article has 4 authors:Reviewed by ScreenIT
-
Infected surfaces as a source of transmissible material in healthcare settings dealing with COVID-19 patients
This article has 15 authors:Reviewed by ScreenIT
-
Rapid expansion of SARS-CoV-2 variants of concern is a result of adaptive epistasis
This article has 8 authors:Reviewed by ScreenIT
-
Peptide Scanning of SARS-CoV and SARS-CoV-2 Spike Protein Subunit 1 Reveals Potential Additional Receptor Binding Sites
This article has 6 authors:Reviewed by ScreenIT
-
Screening of cell-virus, cell-cell, gene-gene cross-talks among kingdoms of life at single cell resolution
This article has 31 authors:Reviewed by ScreenIT
-
Historically High Excess Mortality During the COVID-19 Pandemic in Switzerland, Sweden, and Spain
This article has 10 authors:Reviewed by ScreenIT
-
The fomite contribution to the transmission of COVID-19 in the UK: an evolutionary population estimate
This article has 1 author:Reviewed by ScreenIT
-
Covid-19 vaccine immunogenicity in people living with HIV-1
This article has 12 authors:Reviewed by ScreenIT
-
Mathematical modelling of vaccination rollout and NPIs lifting on COVID-19 transmission with VOC: a case study in Toronto, Canada
This article has 10 authors:Reviewed by ScreenIT
-
Automated ELISA On-Chip for the Detection of Anti-SARS-CoV-2 Antibodies
This article has 15 authors:Reviewed by ScreenIT