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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Analysis of internet trends related to medications for COVID-19 in ten countries with the highest number of cases
This article has 2 authors:Reviewed by ScreenIT
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Defining the Syrian hamster as a highly susceptible preclinical model for SARS-CoV-2 infection
This article has 16 authors:Reviewed by ScreenIT
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Identification on Admission of COVID-19 Patients at Risk of Subsequent Rapid Clinical Deterioration
This article has 9 authors:Reviewed by ScreenIT
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Variability of Individual Infectiousness Derived from Aggregate Statistics of COVID-19
This article has 2 authors:Reviewed by ScreenIT
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Features of α-HBDH in COVID-19 patients with different ages,outcomes and clinical types: a cohort study
This article has 8 authors:Reviewed by ScreenIT
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Patient characteristics, clinical care, resource use, and outcomes associated with hospitalization for COVID-19 in the Toronto area
This article has 18 authors:Reviewed by ScreenIT
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When might host heterogeneity drive the evolution of asymptomatic, pandemic coronaviruses?
This article has 5 authors:Reviewed by ScreenIT
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Sensitive detection and quantification of SARS-CoV-2 in saliva
This article has 27 authors:Reviewed by ScreenIT
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Viral Variants and Vaccinations: If We Can Change the COVID-19 Vaccine… Should We?
This article has 1 author:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Rapid characterization of the propagation of COVID-19 in different countries
This article has 4 authors:Reviewed by ScreenIT