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
-
Computed tomography features of COVID-19 in children
This article has 7 authors:Reviewed by ScreenIT
-
Thirty-Day Outcomes of Children and Adolescents With COVID-19: An International Experience
This article has 42 authors:Reviewed by ScreenIT
-
The Effect of the COVID-19 Pandemic on the Economics of United States Emergency Care
This article has 10 authors:Reviewed by ScreenIT
-
Superspreading Events Without Superspreaders: Using High Attack Rate Events to Estimate N º for Airborne Transmission of COVID-19
This article has 3 authors:Reviewed by ScreenIT
-
Mental Health during the COVID-19 Crisis in Africa: A Systematic Review and Meta-Analysis
This article has 12 authors:Reviewed by ScreenIT
-
Indoor transmission of SARS‐CoV‐2
This article has 6 authors:Reviewed by ScreenIT
-
COVID-19 Fatality and Comorbidity Risk Factors among Diagnosed Patients in Mexico
This article has 2 authors:Reviewed by ScreenIT
-
The furin cleavage site of SARS-CoV-2 spike protein is a key determinant for transmission due to enhanced replication in airway cells
This article has 20 authors:Reviewed by ScreenIT
-
Cleaning and Re-Use of cobas® 6800/8800 Processing Plates for the SARS-CoV-2 Assay
This article has 5 authors:Reviewed by ScreenIT
-
Recurrent Dissemination of SARS-CoV-2 Through the Uruguayan–Brazilian Border
This article has 37 authors:Reviewed by ScreenIT