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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Spatial temporal distribution of COVID-19 risk during the early phase of the pandemic in Malawi
This article has 4 authors:Reviewed by ScreenIT
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Differential impact of mitigation policies and socioeconomic status on COVID-19 prevalence and social distancing in the United States
This article has 6 authors:Reviewed by ScreenIT
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INNOVATION OF AUDIO-VISUAL TRIAGE SYSTEM TO COMBAT THE SPREAD OF COVID-19 INFECTION AND ITS EFFICACY: A NOVEL STRATEGY
This article has 5 authors:Reviewed by ScreenIT
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In vitro: Natural Compounds (Thymol, Carvacrol, Hesperidine, And Thymoquinone) Against Sars-Cov2 Strain Isolated From Egyptian Patients
This article has 8 authors:Reviewed by ScreenIT
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COVID-19 incidence and mortality in the Metropolitan Region, Chile: Time, space, and structural factors
This article has 4 authors:Reviewed by ScreenIT
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Predicting the evolution and control of the COVID-19 pandemic in Portugal
This article has 2 authors:Reviewed by ScreenIT
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Ethnic and socioeconomic differences in SARS-CoV-2 infection: prospective cohort study using UK Biobank
This article has 12 authors:Reviewed by ScreenIT
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Knowledge and perceptions of COVID-19 among government employees in Ethiopia
This article has 6 authors:Reviewed by ScreenIT
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Topoisomerase 1 inhibition therapy protects against SARS-CoV-2-induced inflammation and death in animal models
This article has 51 authors:Reviewed by ScreenIT
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Seroprevalence and attainment of herd immunity against SARS CoV-2
This article has 5 authors:Reviewed by ScreenIT