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
-
Assessing the influence of climate on wintertime SARS-CoV-2 outbreaks
This article has 5 authors:Reviewed by ScreenIT
-
SARS-CoV-2 can recruit a heme metabolite to evade antibody immunity
This article has 40 authors:Reviewed by ScreenIT
-
The Epidemiology Workbench: a Tool for Communities to Strategize in Response to COVID-19 and other Infectious Diseases
This article has 2 authors:Reviewed by ScreenIT
-
Optimal strategies for quarantine stopping in France – General expected patterns of strategies focusing on contact between age groups
This article has 3 authors:Reviewed by ScreenIT
-
Hitting the diagnostic sweet spot: Point-of-care SARS-CoV-2 salivary antigen testing with an off-the-shelf glucometer
This article has 8 authors:Reviewed by ScreenIT, Rapid Reviews Infectious Diseases
-
Using past and current data to estimate potential crisis service use in mental healthcare after the COVID-19 lockdown: South London and Maudsley data
This article has 2 authors:Reviewed by ScreenIT
-
Is Higher Viral Load in SARS-CoV-2 Associated with Death?
This article has 3 authors:Reviewed by ScreenIT
-
Accounting for incomplete testing in the estimation of epidemic parameters
This article has 2 authors:Reviewed by ScreenIT
-
Twitter-based analysis reveals differential COVID-19 concerns across areas with socioeconomic disparities
This article has 5 authors:Reviewed by ScreenIT
-
Testing out of quarantine
This article has 6 authors:Reviewed by ScreenIT