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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Impact of COVID-19 lockdown policy on homicide, suicide, and motor vehicle deaths in Peru
This article has 2 authors:Reviewed by ScreenIT
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Theoretical Epidemic Laws Based on Data of COVID-19 Pandemic
This article has 1 author:Reviewed by ScreenIT
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Dysregulation of Pulmonary Responses in Severe COVID-19
This article has 2 authors:Reviewed by ScreenIT
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Efficient sample pooling strategies for COVID-19 data gathering
This article has 1 author:Reviewed by ScreenIT
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Losartan promotes cell survival following SARS-CoV-2 infection in vitro
This article has 7 authors:Reviewed by ScreenIT
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Cost-effectiveness of Remdesivir and Dexamethasone for COVID-19 Treatment in South Africa
This article has 10 authors:Reviewed by ScreenIT
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Predictability of COVID-19 Hospitalizations, Intensive Care Unit Admissions, and Respiratory Assistance in Portugal: Longitudinal Cohort Study
This article has 3 authors:Reviewed by ScreenIT
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Identification of four linear B-cell epitopes on the SARS-CoV-2 spike protein able to elicit neutralizing antibodies
This article has 27 authors:Reviewed by ScreenIT
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The COVID-19 Pandemic Impact on Primary Health Care services: An Experience from Qatar
This article has 6 authors:Reviewed by ScreenIT
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Modeling the role of clusters and diffusion in the evolution of COVID-19 infections during lock-down
This article has 3 authors:Reviewed by ScreenIT