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
-
The incidence and severity of COVID-19 in adult professional soccer players in Russia
This article has 14 authors:Reviewed by ScreenIT
-
Population-based seroprevalence of SARS-CoV-2 and the herd immunity threshold in Maranhão
This article has 21 authors:Reviewed by ScreenIT
-
Predicting Long-term Evolution of COVID-19 by On-going Data using Bayesian Susceptible-Infected-Removed Model
This article has 2 authors:Reviewed by ScreenIT
-
BayesSMILES: Bayesian Segmentation Modeling for Longitudinal Epidemiological Studies
This article has 4 authors:Reviewed by ScreenIT
-
Lack of Association Between Genetic Variants at ACE2 and TMPRSS2 Genes Involved in SARS-CoV-2 Infection and Human Quantitative Phenotypes
This article has 12 authors:Reviewed by ScreenIT
-
A New Mathematical Approach for the Estimation of epidemic Model Parameters with Demonstration on COVID-19 Pandemic in Libya
This article has 2 authors:Reviewed by ScreenIT
-
Wisconsin April 2020 Election Not Associated with Increase in COVID-19 Infection Rates
This article has 3 authors:Reviewed by ScreenIT
-
Biomimetic Virus-like Particles as SARS-CoV-2 Positive Controls for RT-PCR Diagnostics
This article has 6 authors:Reviewed by ScreenIT
-
Use of the first National Early Warning Score recorded within 24 hours of admission to estimate the risk of in-hospital mortality in unplanned COVID-19 patients: a retrospective cohort study
This article has 5 authors:Reviewed by ScreenIT
-
COVID-19 Case Series at UnityPoint Health St. Luke’s Hospital in Cedar Rapids, IA
This article has 2 authors:Reviewed by ScreenIT