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
-
Meta-Analysis of Several Epidemic Characteristics of COVID-19
This article has 3 authors:Reviewed by ScreenIT
-
Reduction in stroke patients’ referral to the ED in the COVID-19 era: A four-year comparative study
This article has 4 authors:Reviewed by ScreenIT
-
COVID-SGIS: A Smart Tool for Dynamic Monitoring and Temporal Forecasting of Covid-19
This article has 15 authors:Reviewed by ScreenIT
-
Does death from Covid-19 arise from a multi-step process?
This article has 10 authors:Reviewed by ScreenIT
-
The COVID-19 Pandemic in Africa: Predictions using the SIR Model
This article has 6 authors:Reviewed by ScreenIT
-
Hospital readmissions of discharged patients with COVID-19
This article has 10 authors:Reviewed by ScreenIT
-
Tocilizumab for Treatment of Mechanically Ventilated Patients With COVID-19
This article has 22 authors:Reviewed by ScreenIT
-
Characterizing and Forecasting Emergency Department Visits Related to COVID-19 Using Chief Complaints and Discharge Diagnoses
This article has 5 authors:Reviewed by ScreenIT
-
How Efficient Can Non-Professional Masks Suppress COVID-19 Pandemic?
This article has 2 authors:Reviewed by ScreenIT
-
Missing clinical trial data: the evidence gap in primary data for potential COVID-19 drugs
This article has 4 authors:Reviewed by ScreenIT