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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Quality controlled SARS-CoV-2 duplex procedure to reduce time and scarce molecular biology diagnosis reagents
This article has 4 authors:Reviewed by ScreenIT
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Susceptibility of well-differentiated airway epithelial cell cultures from domestic and wildlife animals to SARS-CoV-2
This article has 27 authors:Reviewed by ScreenIT
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Early impact of the coronavirus disease (COVID-19) pandemic and physical distancing measures on routine childhood vaccinations in England, January to April 2020
This article has 13 authors:Reviewed by ScreenIT
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Pathogenic perspective of missense mutations of ORF3a protein of SARS-CoV-2
This article has 5 authors:Reviewed by ScreenIT
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Efficacy and Safety of Ivermectin and Hydroxychloroquine in Patients with Severe COVID-19: A Randomized Controlled Trial
This article has 13 authors:Reviewed by ScreenIT
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Development and Validation of a Web-Based Severe COVID-19 Risk Prediction Model
This article has 9 authors:Reviewed by ScreenIT
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Emergence and spread of a SARS-CoV-2 variant through Europe in the summer of 2020
This article has 19 authors:Reviewed by ScreenIT
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Seroprevalence of anti‐SARS‐CoV‐2 IgG antibodies in children with household exposure to adults with COVID‐19: Preliminary findings
This article has 15 authors:Reviewed by ScreenIT
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Incidence of SARS-CoV-2 infection among asymptomatic frontline health workers in Los Angeles County, California
This article has 17 authors:Reviewed by ScreenIT
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COVID-19 serology in nephrology healthcare workers
This article has 15 authors:Reviewed by ScreenIT