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
-
Early Detection and Assessment of Covid-19
This article has 2 authors:Reviewed by ScreenIT
-
Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic
This article has 2 authors:Reviewed by ScreenIT
-
The distress of Iranian adults during the Covid-19 pandemic – More distressed than the Chinese and with different predictors
This article has 5 authors:Reviewed by ScreenIT
-
Community responses during early phase of the COVID-19 epidemic: a cross-sectional study
This article has 7 authors:Reviewed by ScreenIT
-
Predict the next moves of COVID-19: reveal the temperate and tropical countries scenario
This article has 2 authors:Reviewed by ScreenIT
-
Plasma metabolomic and lipidomic alterations associated with COVID-19
This article has 23 authors:Reviewed by ScreenIT
-
Explaining the “Bomb-Like” Dynamics of COVID-19 with Modeling and the Implications for Policy
This article has 11 authors:Reviewed by ScreenIT
-
Estimating number of cases and spread of coronavirus disease (COVID-19) using critical care admissions, United Kingdom, February to March 2020
This article has 7 authors:Reviewed by ScreenIT
-
COVID-19 higher induced mortality in Chinese regions with lower air quality
This article has 2 authors:Reviewed by ScreenIT
-
A hybrid multi-scale model of COVID-19 transmission dynamics to assess the potential of non-pharmaceutical interventions
This article has 2 authors:Reviewed by ScreenIT