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
-
Genomic and Epidemiological Analysis of SARS-CoV-2 Viruses in Sri Lanka
This article has 15 authors:Reviewed by ScreenIT
-
Illness duration and symptom profile in symptomatic UK school-aged children tested for SARS-CoV-2
This article has 22 authors:Reviewed by ScreenIT
-
SARS-CoV-2 infections and hospitalisations among immigrants in Norway-significance of occupation, household crowding, education, household income and medical risk: a nationwide register study
This article has 8 authors:Reviewed by ScreenIT
-
Optimal dose and safety of molnupiravir in patients with early SARS-CoV-2: a Phase I, open-label, dose-escalating, randomized controlled study
This article has 38 authors:Reviewed by ScreenIT
-
Key factors affecting people’s unwillingness to be confined during the COVID-19 pandemic in Spain: a large-scale population study
This article has 6 authors:Reviewed by ScreenIT
-
Optimized Quantification of Intrahost Viral Diversity in SARS-CoV-2 and Influenza Virus Sequence Data
This article has 20 authors:Reviewed by ScreenIT
-
Seroprevalence of SARS-CoV-2 antibodies in social housing areas in Denmark
This article has 35 authors:Reviewed by ScreenIT
-
Semi-supervised identification of SARS-CoV-2 molecular targets
This article has 8 authors:Reviewed by ScreenIT
-
Results of an Academic Dialysis Program-Wide SARS-CoV-2 Vaccination Effort
This article has 4 authors:Reviewed by ScreenIT
-
In silico and in vitro Demonstration of Homoharrintonine’s Antagonism of RBD-ACE2 Binding and its Anti-inflammatory and anti-thrombogenic Properties in a 3D human vascular lung model
This article has 9 authors:Reviewed by ScreenIT