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
-
Shared B cell memory to coronaviruses and other pathogens varies in human age groups and tissues
This article has 19 authors:Reviewed by ScreenIT
-
A computational analysis on Covid-19 transmission raises imuuno-epidemiology concerns
This article has 2 authors:Reviewed by ScreenIT
-
Human cardiosphere-derived stromal cells exposed to SARS-CoV-2 evolve into hyper-inflammatory/ pro -fibrotic phenotype and produce infective viral particles depending on the levels of ACE2 receptor expression
This article has 17 authors:Reviewed by ScreenIT
-
Parents’ and guardians’ views and experiences of accessing routine childhood vaccinations during the coronavirus (COVID-19) pandemic: A mixed methods study in England
This article has 4 authors:Reviewed by ScreenIT
-
When Resources Are Scarce - Feasibility of Emergency Ventilation of Two Patients With One Ventilator
This article has 6 authors:Reviewed by ScreenIT
-
Nosocomial Outbreak of SARS-CoV-2 in a “Non-COVID-19” Hospital Ward: Virus Genome Sequencing as a Key Tool to Understand Cryptic Transmission
This article has 13 authors: -
Model for evaluating cost-effectiveness of surveillance testing for SARS-CoV2
This article has 1 author:Reviewed by ScreenIT
-
Association of the infection probability of COVID-19 with ventilation rates in confined spaces
This article has 2 authors:Reviewed by ScreenIT
-
Two mutations in the SARS-CoV-2 spike protein and RNA polymerase complex are associated with COVID-19 mortality risk
This article has 21 authors:Reviewed by ScreenIT
-
Ethnic differences in COVID-19 mortality during the first two waves of the Coronavirus Pandemic: a nationwide cohort study of 29 million adults in England
This article has 9 authors:Reviewed by ScreenIT