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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Effect of pre-exposure use of hydroxychloroquine on COVID-19 mortality: a population-based cohort study in patients with rheumatoid arthritis or systemic lupus erythematosus using the OpenSAFELY platform
This article has 33 authors:Reviewed by ScreenIT
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Differential effects of intervention timing on COVID-19 spread in the United States
This article has 3 authors:Reviewed by ScreenIT
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The Impact of COVID-19 Lockdown on Diabetes Complication and Diabetes Management in People With Diabetes in Indonesia
This article has 5 authors:Reviewed by ScreenIT
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Effect of RBD mutation (Y453F) in spike glycoprotein of SARS-CoV-2 on neutralizing antibody affinity
This article has 3 authors:Reviewed by ScreenIT
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Prevalence of Face Mask Wearing in Northern Vermont in Response to the COVID-19 Pandemic
This article has 3 authors:Reviewed by ScreenIT
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Indirect acute effects of the COVID-19 pandemic on physical and mental health in the UK: a population-based study
This article has 21 authors:Reviewed by ScreenIT
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Climate and the spread of COVID-19
This article has 7 authors:Reviewed by ScreenIT
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Exploring beyond clinical routine SARS-CoV-2 serology using MultiCoV-Ab to evaluate endemic coronavirus cross-reactivity
This article has 36 authors:Reviewed by ScreenIT
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Impact of COVID-19 restrictions on the postpartum experience of women living in Eastern Canada: A mixed method cohort study
This article has 6 authors:Reviewed by ScreenIT
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Stress symptoms and reactions to COVID-19: A multinational survey from six Asian regions
This article has 4 authors:Reviewed by ScreenIT