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
-
Relative Pandemic Severity in Canada and Four Peer Nations During the SARS-CoV-2 Pandemic
This article has 5 authors:Reviewed by ScreenIT
-
Impact of national and regional lockdowns on COVID-19 epidemic waves: Application to the 2020 spring wave in France
This article has 5 authors:Reviewed by ScreenIT
-
A SARS-CoV-2 vaccine candidate would likely match all currently circulating variants
This article has 12 authors:Reviewed by ScreenIT
-
Structural dynamics of the β-coronavirus M pro protease ligand binding sites
This article has 16 authors:Reviewed by ScreenIT
-
Situation of COVID-19 in Brazil in August 2020: An Analysis via Growth Models as Implemented in the ModInterv System for Monitoring the Pandemic
This article has 6 authors:Reviewed by ScreenIT
-
"Relationship of Liver Enzyme Levels with the Clinical Course of Covid-19"
This article has 1 author:Reviewed by ScreenIT
-
Pulmonary fibrosis 4 months after COVID-19 is associated with severity of illness and blood leucocyte telomere length
This article has 9 authors:Reviewed by ScreenIT
-
Mortality and critical care unit admission associated with the SARS-CoV-2 lineage B.1.1.7 in England: an observational cohort study
This article has 12 authors:Reviewed by ScreenIT
-
Dynamics of severe acute respiratory syndrome coronavirus 2 genome variants in the feces during convalescence
This article has 12 authors:Reviewed by ScreenIT
-
6-month mortality and readmissions of hospitalized COVID-19 patients: A nationwide cohort study of 8,679 patients in Germany
This article has 9 authors:Reviewed by ScreenIT