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
-
Is the vitamin D status of patients with COVID-19 associated with reduced mortality? A systematic review and meta-analysis
This article has 4 authors:Reviewed by ScreenIT
-
Smoking and E-Cigarette Use Among U.S. Adults During the COVID-19 Pandemic
This article has 3 authors:Reviewed by ScreenIT
-
Persistence of symptoms up to 10 months following acute COVID-19 illness
This article has 12 authors:Reviewed by ScreenIT
-
GRAd-COV2, a gorilla adenovirus-based candidate vaccine against COVID-19, is safe and immunogenic in younger and older adults
This article has 37 authors:Reviewed by ScreenIT
-
One-shot identification of SARS-CoV-2 S RBD escape mutants using yeast screening
This article has 12 authors:Reviewed by ScreenIT
-
A small number of early introductions seeded widespread transmission of SARS-CoV-2 in Québec, Canada
This article has 24 authors:Reviewed by ScreenIT
-
Hypercoagulation Detected by Rotational Thromboelastometry Predicts Mortality in COVID-19: A Risk Model Based on a Prospective Observational Study
This article has 9 authors:Reviewed by ScreenIT
-
SARS-CoV-2 UK, South African and Brazilian Variants in Karachi- Pakistan
This article has 6 authors:Reviewed by ScreenIT
-
Leg-heel chest compression as an alternative for medical professionals in times of COVID-19
This article has 8 authors:Reviewed by ScreenIT
-
Impacts of Morally Distressing Experiences on the Mental Health of Canadian Health Care Workers During the COVID-19 Pandemic
This article has 22 authors:Reviewed by ScreenIT