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
-
Magnitude and time-course of excess mortality during COVID-19 outbreak: population-based empirical evidence from highly impacted provinces in northern Italy
This article has 15 authors:Reviewed by ScreenIT
-
The diagnostic accuracy of isothermal nucleic acid point-of-care tests for human coronaviruses: A systematic review and meta-analysis
This article has 3 authors:Reviewed by ScreenIT
-
Psychological state and family functioning of University of Ibadan students during the COVID-19 lockdown
This article has 1 author:Reviewed by ScreenIT
-
Genomic epidemiology reveals multiple introductions and spread of SARS-CoV-2 in the Indian state of Karnataka
This article has 20 authors:Reviewed by ScreenIT
-
Weak correlation between antibody titers and neutralizing activity in sera from SARS‐CoV‐2 infected subjects
This article has 10 authors:Reviewed by ScreenIT
-
Estimating the time-varying reproduction number of COVID-19 with a state-space method
This article has 3 authors:Reviewed by ScreenIT
-
Eurofins Covid-19 Sentinel™ Wastewater Test Provide Early Warning of a potential COVID-19 outbreak
This article has 5 authors:Reviewed by ScreenIT
-
What can the ideal gas say about global pandemics? Reinterpreting the basic reproduction number
This article has 1 author:Reviewed by ScreenIT
-
Stabilizing the closed SARS-CoV-2 spike trimer
This article has 9 authors:Reviewed by ScreenIT
-
Analysis of Inactivation of SARS-CoV-2 by Specimen Transport Media, Nucleic Acid Extraction Reagents, Detergents, and Fixatives
This article has 17 authors:Reviewed by ScreenIT