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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Characterizing Transcriptional Regulatory Sequences in Coronaviruses and Their Role in Recombination
This article has 4 authors:Reviewed by ScreenIT
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Transcriptomic similarities and differences in host response between SARS-CoV-2 and other viral infections
This article has 19 authors:Reviewed by ScreenIT
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Chloroquine, but not hydroxychlorquine, prolongs the QT interval in a primary care population
This article has 6 authors:Reviewed by ScreenIT
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The Enzymatic Activity of the nsp14 Exoribonuclease Is Critical for Replication of MERS-CoV and SARS-CoV-2
This article has 6 authors:Reviewed by ScreenIT
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Prognostic factors in Spanish COVID-19 patients: A case series from Barcelona
This article has 12 authors:Reviewed by ScreenIT
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Distress among Brazilian university students due to the Covid-19 pandemic: survey results and reflections
This article has 3 authors:Reviewed by ScreenIT
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Clozapine treatment and risk of COVID-19 infection: retrospective cohort study
This article has 5 authors:Reviewed by ScreenIT
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Epidemiological characterisation of asymptomatic carriers of COVID-19 in Colombia: a cross-sectional study
This article has 12 authors:Reviewed by ScreenIT
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The influence of comorbidity on the severity of COVID-19 disease: A systematic review and analysis
This article has 4 authors:Reviewed by ScreenIT
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Cardiometabolic Traits, Sepsis, and Severe COVID-19
This article has 21 authors:Reviewed by ScreenIT