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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Occupational and environmental exposure to SARS-CoV-2 in and around infected mink farms
This article has 20 authors:Reviewed by ScreenIT
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Genomic epidemiology of SARS-CoV-2 in Esteio, Rio Grande do Sul, Brazil
This article has 16 authors:Reviewed by ScreenIT
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Syncope and COVID-19 disease – A systematic review
This article has 6 authors:Reviewed by ScreenIT
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SARS-CoV-2 infected cells present HLA-I peptides from canonical and out-of-frame ORFs
This article has 21 authors:Reviewed by ScreenIT
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SARS-CoV-2 Detection with De Novo-Designed Synthetic Riboregulators
This article has 11 authors:Reviewed by ScreenIT
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Risk factors for outbreaks of SARS-CoV-2 infection at retirement homes in Ontario, Canada: a population-level cohort study
This article has 14 authors:Reviewed by ScreenIT
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SARS-CoV-2 infection paralyzes cytotoxic and metabolic functions of the immune cells
This article has 10 authors:Reviewed by ScreenIT
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Effectiveness of booster BCG vaccination in preventing Covid-19 infection
This article has 6 authors:Reviewed by ScreenIT
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Comprehensive identification and isolation policies have effectively suppressed the spread of COVID-19
This article has 3 authors:Reviewed by ScreenIT
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Persisting Neutralizing Activity to SARS-CoV-2 over Months in Sera of COVID-19 Patients
This article has 12 authors:Reviewed by ScreenIT