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
-
Second week methyl-prednisolone pulses improve prognosis in patients with severe coronavirus disease 2019 pneumonia: An observational comparative study using routine care data
This article has 14 authors:Reviewed by ScreenIT
-
Prognostic Factors of Initial Chest CT Findings for ICU Admission and Mortality in Patients with COVID-19 Pneumonia
This article has 10 authors:Reviewed by ScreenIT
-
SARS-CoV-2 Nucleocapsid protein is decorated with multiple N- and O-glycans
This article has 6 authors:Reviewed by ScreenIT
-
Vaccinating Australia: How long will it take?
This article has 5 authors:Reviewed by ScreenIT
-
Estimation of Tunisia COVID-19 infected cases based on mortality rate
This article has 2 authors:Reviewed by ScreenIT
-
The successful use of volunteers to enhance NHS Test and Trace contact tracing of in-patients with Covid-19: a Pilot Study
This article has 8 authors:Reviewed by ScreenIT
-
Furin Cleavage Site Is Key to SARS-CoV-2 Pathogenesis
This article has 29 authors:Reviewed by ScreenIT
-
Challenges and opportunities of the COVID-19 pandemic for perinatal mental health care: a mixed-methods study of mental health care staff
This article has 6 authors:Reviewed by ScreenIT
-
How Policies on Restaurants, Bars, Nightclubs, Masks, Schools, and Travel Influenced Swiss COVID-19 Reproduction Ratios
This article has 5 authors:Reviewed by ScreenIT
-
Development of a Saliva-Optimized RT-LAMP Assay for SARS-CoV-2
This article has 7 authors:Reviewed by ScreenIT