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
-
Master Regulator Analysis of the SARS-CoV-2/Human Interactome
This article has 4 authors:Reviewed by ScreenIT
-
Engineering human ACE2 to optimize binding to the spike protein of SARS coronavirus 2
This article has 8 authors:Reviewed by ScreenIT
-
Multiple approaches for massively parallel sequencing of SARS-CoV-2 genomes directly from clinical samples
This article has 34 authors:Reviewed by ScreenIT
-
Epidemiological Trends of Coronavirus Disease 2019 in China
This article has 6 authors:Reviewed by ScreenIT
-
Assessment of public attention, risk perception, emotional and behavioural responses to the COVID-19 outbreak: social media surveillance in China
This article has 5 authors:Reviewed by ScreenIT
-
Unprecedented disruption of lives and work: Health, distress and life satisfaction of working adults in China one month into the COVID-19 outbreak
This article has 4 authors:Reviewed by ScreenIT
-
Spread of SARS-CoV-2 Coronavirus likely constrained by climate
This article has 2 authors:Reviewed by ScreenIT
-
Predictive symptoms and comorbidities for severe COVID-19 and intensive care unit admission: a systematic review and meta-analysis
This article has 2 authors:Reviewed by ScreenIT
-
Clinical and epidemiological characteristics of pediatric SARS-CoV-2 infections in China: A multicenter case series
This article has 7 authors:Reviewed by ScreenIT
-
Ocular manifestations and clinical characteristics of 535 cases of COVID‐19 in Wuhan, China: a cross‐sectional study
This article has 10 authors:Reviewed by ScreenIT