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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The global distribution of COVID-19 vaccine: The role of macro-socioeconomics measures
This article has 2 authors:Reviewed by ScreenIT
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SARS-CoV-2 ORF9c Is a Membrane-Associated Protein that Suppresses Antiviral Responses in Cells
This article has 13 authors:Reviewed by ScreenIT
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High Rate of SARS-CoV-2 Transmission Due to Choir Practice in France at the Beginning of the COVID-19 Pandemic
This article has 1 author:Reviewed by ScreenIT
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Mathematical Modelling Projections Versus the Actual Course of the COVID-19 Epidemic following the Nationwide Lockdown in Kyrgyzstan
This article has 11 authors:Reviewed by ScreenIT
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Time, space and social interactions: exit mechanisms for the Covid-19 epidemics
This article has 7 authors:Reviewed by ScreenIT
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idCOV: a pipeline for quick clade identification of SARS-CoV-2 isolates
This article has 4 authors:Reviewed by ScreenIT
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Identification of COVID-19 subtypes based on immunogenomic profiling
This article has 4 authors:Reviewed by ScreenIT
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Persistent Bacterial Coinfection of a COVID-19 Patient Caused by a Genetically Adapted Pseudomonas aeruginosa Chronic Colonizer
This article has 14 authors:Reviewed by ScreenIT
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Effect of Dry Heat and Autoclave Decontamination Cycles on N95 FFRs
This article has 9 authors:Reviewed by ScreenIT
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Prospective Comparison of Saliva and Nasopharyngeal Swab Sampling for Mass Screening for COVID-19
This article has 22 authors:Reviewed by ScreenIT