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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Sustainable targeted interventions to mitigate the COVID-19 pandemic: A big data-driven modeling study in Hong Kong
This article has 5 authors:Reviewed by ScreenIT
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Identifying novel factors associated with COVID-19 transmission and fatality using the machine learning approach
This article has 12 authors:Reviewed by ScreenIT
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The Duration, Dynamics, and Determinants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antibody Responses in Individual Healthcare Workers
This article has 243 authors:Reviewed by ScreenIT
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Preparedness and Mitigation by projecting the risk against COVID-19 transmission using Machine Learning Techniques
This article has 4 authors:Reviewed by ScreenIT
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COVID-19 prevalence estimation by random sampling in population - optimal sample pooling under varying assumptions about true prevalence
This article has 1 author:Reviewed by ScreenIT
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Factors Associated with Timely Test Seeking, Test Turnaround, and Public Reporting of COVID-19: a retrospective analysis in Ontario, Canada
This article has 5 authors:Reviewed by ScreenIT
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Indirect Impact of the COVID-19 Pandemic on Activity and Outcomes of Transcatheter and Surgical Treatment of Aortic Stenosis in England
This article has 11 authors:Reviewed by ScreenIT
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Comparative Performance of SARS-CoV-2 Detection Assays Using Seven Different Primer-Probe Sets and One Assay Kit
This article has 10 authors:Reviewed by ScreenIT
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Genetic and non-genetic factors affecting the expression of COVID-19-relevant genes in the large airway epithelium
This article has 45 authors:Reviewed by ScreenIT
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Early COVID-19 therapy with azithromycin plus nitazoxanide, ivermectin or hydroxychloroquine in outpatient settings significantly improved COVID-19 outcomes compared to known outcomes in untreated patients
This article has 4 authors:Reviewed by ScreenIT