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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Development of a Synthetic Poxvirus-Based SARS-CoV-2 Vaccine
This article has 20 authors:Reviewed by ScreenIT
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Interleukin-3 is a predictive marker for severity and outcome during SARS-CoV-2 infections
This article has 31 authors:Reviewed by ScreenIT
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Utility of the ROX Index in Predicting Intubation for Patients With COVID-19–Related Hypoxemic Respiratory Failure Receiving High-Flow Nasal Therapy: Retrospective Cohort Study
This article has 18 authors:Reviewed by ScreenIT
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Relative COVID-19 Viral Persistence and Antibody Kinetics
This article has 10 authors:Reviewed by ScreenIT
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Broad phenotypic alterations and potential dysfunction of lymphocytes in individuals clinically recovered from COVID-19
This article has 18 authors:Reviewed by ScreenIT
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Identifying main and interaction effects of risk factors to predict intensive care admission in patients hospitalized with COVID-19: a retrospective cohort study in Hong Kong
This article has 10 authors:Reviewed by ScreenIT
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Socioeconomic factors analysis for COVID-19 US reopening sentiment with Twitter and census data
This article has 7 authors:Reviewed by ScreenIT
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Clinical characterization of respiratory large droplet production during common airway procedures using high-speed imaging
This article has 9 authors:Reviewed by ScreenIT
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Multianalyte serology in home-sampled blood enables an unbiased assessment of the immune response against SARS-CoV-2
This article has 21 authors:Reviewed by ScreenIT
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Evaluation of procalcitonin as a contribution to antimicrobial stewardship in SARS-CoV-2 infection: a retrospective cohort study
This article has 10 authors:Reviewed by ScreenIT