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
-
Engineered unnatural ubiquitin for optimal detection of deubiquitinating enzymes
This article has 6 authors:Reviewed by ScreenIT
-
Exploring overcrowding trends in an inner city emergence department in the UK before and during COVID-19 epidemic
This article has 6 authors:Reviewed by ScreenIT
-
Cohort profile: SARS-CoV-2/COVID-19 hospitalised patients in Switzerland
This article has 28 authors:Reviewed by ScreenIT
-
Self-sampling of capillary blood for SARS-CoV-2 serology
This article has 19 authors:Reviewed by ScreenIT
-
COVID-19 control measure effects suggest excess winter mortality is more sensitive to infection control than warmer temperatures
This article has 4 authors:Reviewed by ScreenIT
-
Network-based Virus-Host Interaction Prediction with Application to SARS-CoV-2
This article has 4 authors:Reviewed by ScreenIT
-
Field-deployable, rapid diagnostic testing of saliva for SARS-CoV-2
This article has 20 authors:Reviewed by ScreenIT
-
Sensitivity of ID NOW and RT–PCR for detection of SARS-CoV-2 in an ambulatory population
This article has 3 authors:This article has been curated by 1 group: -
A pandemic at the Tunisian scale. Mathematical modelling of reported and unreported COVID-19 infected cases
This article has 1 author:Reviewed by ScreenIT
-
COPD in the time of COVID-19: an analysis of acute exacerbations and reported behavioural changes in patients with COPD
This article has 7 authors:Reviewed by ScreenIT