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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Prolonged SARS-CoV-2 cell culture replication in respiratory samples from patients with severe COVID-19
This article has 5 authors:Reviewed by ScreenIT
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Viral Dynamics of SARS-CoV-2 Variants in Vaccinated and Unvaccinated Persons
This article has 19 authors:Reviewed by ScreenIT
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Delivery of cardiology services in Africa during the COVID-19 pandemic: what should we expect after this pandemic?
This article has 16 authors:Reviewed by ScreenIT
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Increased Prolonged Sitting in Patients with Rheumatoid Arthritis during the COVID-19 Pandemic: A Within-Subjects, Accelerometer-Based Study
This article has 11 authors:Reviewed by ScreenIT
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Secondary haemophagocytic lymphohistiocytosis in hospitalised COVID-19 patients as indicated by a modified HScore is infrequent and high scores do not associate with increased mortality
This article has 9 authors:Reviewed by ScreenIT
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Identification of Inhibitors of SARS-CoV-2 3CL-Pro Enzymatic Activity Using a Small Molecule in Vitro Repurposing Screen
This article has 33 authors:Reviewed by ScreenIT
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Frequency and accuracy of proactive testing for COVID-19
This article has 3 authors:Reviewed by ScreenIT
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Forecasting COVID-19 Dynamics and Endpoint in Bangladesh: A Data-driven Approach
This article has 7 authors:Reviewed by ScreenIT
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The SARS-CoV-2 RNA interactome
This article has 9 authors:Reviewed by ScreenIT
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Surveillance of genetic diversity and evolution in locally transmitted SARS-CoV-2 in Pakistan during the first wave of the COVID-19 pandemic
This article has 6 authors:Reviewed by ScreenIT