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
-
No independent associations between physical activity and clinical outcomes among hospitalized patients with moderate to severe COVID-19
This article has 10 authors:Reviewed by ScreenIT
-
SARS-CoV-2 envelope protein causes acute respiratory distress syndrome (ARDS)-like pathological damages and constitutes an antiviral target
This article has 34 authors:Reviewed by ScreenIT
-
Dynamical SPQEIR model assesses the effectiveness of non-pharmaceutical interventions against COVID-19 epidemic outbreaks
This article has 10 authors:Reviewed by ScreenIT
-
COVID-19 lockdowns cause global air pollution declines
This article has 4 authors:Reviewed by ScreenIT
-
COVID-19 case management: The policy model in Morocco context
This article has 1 author:Reviewed by ScreenIT
-
Nonlinear Markov Chain Modelling of the Novel Coronavirus (Covid-19) Pandemic
This article has 2 authors:Reviewed by ScreenIT
-
Elevated HScore is Associated with Poor Clinical Outcomes in COVID-19, Even in the Absence of Secondary Hemophagocytic Lymphohistiocytosis
This article has 9 authors:Reviewed by ScreenIT
-
The amplified second outbreaks of global COVID-19 pandemic
This article has 9 authors:Reviewed by ScreenIT
-
The effect of ABO blood group and antibody class on the risk of COVID-19 infection and severity of clinical outcomes
This article has 6 authors:Reviewed by ScreenIT
-
Do not attempt cardiopulmonary resuscitation (DNACPR) decisions in people admitted with suspected COVID-19: Secondary analysis of the PRIEST observational cohort study
This article has 4 authors:Reviewed by ScreenIT