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
-
Assessing the risk of vaccine-driven virulence evolution in SARS-CoV-2
This article has 2 authors:Reviewed by ScreenIT
-
Economic impact of the first wave of the COVID-19 pandemic on acute care hospitals in Japan
This article has 16 authors:Reviewed by ScreenIT
-
Deep learning segmentation model for automated detection of the opacity regions in the chest X-rays of the Covid-19 positive patients and the application for disease severity
This article has 4 authors:Reviewed by ScreenIT
-
Assessing required SARS-CoV-2 blanket testing rates for possible control of the outbreak in the epicentre Lusaka province of Zambia with consideration for asymptomatic individuals: A simple mathematical modelling study
This article has 5 authors:Reviewed by ScreenIT
-
Anxiety and depression among people living in quarantine centers during COVID-19 pandemic: A mixed method study from western Nepal
This article has 10 authors:Reviewed by ScreenIT
-
Predictors of clinical deterioration in patients with suspected COVID-19 managed in a ‘virtual hospital’ setting: a cohort study
This article has 8 authors:Reviewed by ScreenIT
-
Role of Immunoglobulin M and A Antibodies in the Neutralization of Severe Acute Respiratory Syndrome Coronavirus 2
This article has 22 authors:Reviewed by ScreenIT
-
Predicting the future SARS-COV-2 reproductive rate
This article has 4 authors:Reviewed by ScreenIT
-
Full lockdown policies in Western Europe countries have no evident impacts on the COVID-19 epidemic
This article has 1 author:Reviewed by ScreenIT
-
SNPnexus COVID: Facilitating the analysis of COVID-19 host genetics
This article has 5 authors:Reviewed by ScreenIT