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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Computational modeling of protein conformational changes - Application to the opening SARS-CoV-2 spike
This article has 4 authors:Reviewed by ScreenIT
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A blueprint for academic laboratories to produce SARS-CoV-2 quantitative RT-PCR test kits
This article has 35 authors:Reviewed by ScreenIT
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COVID-19 disease severity and associated factors among Ethiopian patients: A study of the millennium COVID-19 care center
This article has 13 authors:Reviewed by ScreenIT
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COVID-19, lockdowns and motor vehicle collisions: empirical evidence from Greece
This article has 1 author:Reviewed by ScreenIT
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Complementary methods for SARS-CoV-2 diagnosis in times of material shortage
This article has 10 authors:Reviewed by ScreenIT
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High-throughput SARS-CoV-2 and host genome sequencing from single nasopharyngeal swabs
This article has 42 authors:Reviewed by ScreenIT
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Paradoxical effects of cigarette smoke and COPD on SARS-CoV2 infection and disease
This article has 22 authors:Reviewed by ScreenIT
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Signature of the State measures on the COVID-19 Pandemic in China, Italy, and USA
This article has 1 author:Reviewed by ScreenIT
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Host’s Specific SARS-CoV-2 Mutations: Insertion of the Phenylalanine in the NSP6 Linked to the United Kingdom and Premature Termination of the ORF-8 Associated with the European and the United States of America Derived Samples
This article has 4 authors:Reviewed by ScreenIT
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False-negative results of initial RT-PCR assays for COVID-19: A systematic review
This article has 13 authors:Reviewed by ScreenIT