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
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Influence of nursing staff working hours on stress levels during the COVID-19 pandemic
This article has 3 authors:Reviewed by ScreenIT
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Job Insecurity, Financial Threat, and Mental Health in the COVID-19 Context: The Moderating Role of the Support Network
This article has 5 authors:Reviewed by ScreenIT
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Should international borders re-open? The impact of travel restrictions on COVID-19 importation risk
This article has 5 authors:Reviewed by ScreenIT
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Determination of Robust Regional CT Radiomics Features for COVID-19
This article has 1 author:Reviewed by ScreenIT
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Modeling tempo of COVID ‐19 pandemic in India and significance of lockdown
This article has 2 authors:Reviewed by ScreenIT
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Whole Care Home Testing for Covid-19 in a Local Authority Area in the United Kingdom
This article has 6 authors:Reviewed by ScreenIT
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Routine childhood immunisation during the COVID-19 pandemic in Africa: a benefit–risk analysis of health benefits versus excess risk of SARS-CoV-2 infection
This article has 46 authors:Reviewed by ScreenIT
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Correlates of and changes in aerobic physical activity and strength training before and after the onset of COVID-19 pandemic in the UK: findings from the HEBECO study
This article has 6 authors:Reviewed by ScreenIT
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Obsessive–compulsive symptoms and information seeking during the Covid-19 pandemic
This article has 3 authors:Reviewed by ScreenIT
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A longitudinal study of the impact of human mobility on the incidence of COVID-19 in India
This article has 2 authors:Reviewed by ScreenIT