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
-
The potential SARS-CoV-2 entry inhibitor
This article has 12 authors:Reviewed by ScreenIT
-
Severity of Respiratory Infections With Seasonal Coronavirus Is Associated With Viral and Bacterial Coinfections
This article has 4 authors:Reviewed by ScreenIT
-
Association of diabetes mellitus with disease severity and prognosis in COVID-19: A retrospective cohort study
This article has 15 authors:Reviewed by ScreenIT
-
Acute kidney injury at early stage as a negative prognostic indicator of patients with COVID-19: a hospital-based retrospective analysis
This article has 14 authors:Reviewed by ScreenIT
-
Early chest computed tomography to diagnose COVID-19 from suspected patients: A multicenter retrospective study
This article has 10 authors:Reviewed by ScreenIT
-
Comparison of spatiotemporal characteristics of the COVID-19 and SARS outbreaks in mainland China
This article has 5 authors:Reviewed by ScreenIT
-
Moving-average based index to timely evaluate the current epidemic situation after COVID-19 outbreak
This article has 5 authors:Reviewed by ScreenIT
-
A Multicenter Study of Coronavirus Disease 2019 Outcomes of Cancer Patients in Wuhan, China
This article has 11 authors:Reviewed by ScreenIT
-
Human Leukocyte Antigen Susceptibility Map for Severe Acute Respiratory Syndrome Coronavirus 2
This article has 7 authors:Reviewed by ScreenIT
-
Viral Kinetics and Antibody Responses in Patients with COVID-19
This article has 27 authors:Reviewed by ScreenIT