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
-
SARS-CoV-2 RNA Quantification Using Droplet Digital RT-PCR
This article has 13 authors:Reviewed by ScreenIT
-
The SARS-COV-2 outbreak around the Amazon rainforest: The relevance of the airborne transmission.
This article has 1 author:Reviewed by ScreenIT
-
Ebselen, Disulfiram, Carmofur, PX-12, Tideglusib, and Shikonin Are Nonspecific Promiscuous SARS-CoV-2 Main Protease Inhibitors
This article has 7 authors:Reviewed by ScreenIT
-
Chinese Public's Attention to the COVID-19 Epidemic on Social Media: Observational Descriptive Study
This article has 4 authors:Reviewed by ScreenIT
-
Fear and death anxiety among Latin American doctors during the Covid-19 pandemic
This article has 5 authors:Reviewed by ScreenIT
-
Structural insights into the cross-neutralization of SARS-CoV and SARS-CoV-2 by the human monoclonal antibody 47D11
This article has 11 authors:Reviewed by ScreenIT
-
D614G Mutation Alters SARS-CoV-2 Spike Conformation and Enhances Protease Cleavage at the S1/S2 Junction
This article has 12 authors:Reviewed by ScreenIT
-
A prospective clinical evaluation of a patient isolation hood during the COVID-19 pandemic
This article has 7 authors:Reviewed by ScreenIT
-
Clinical and spatial characteristics of Severe Acute Respiratory Syndrome by COVID-19 in Indigenous of Brazil
This article has 10 authors:Reviewed by ScreenIT
-
COVID-19 dynamics in an Ohio prison
This article has 5 authors:Reviewed by ScreenIT