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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SARS-CoV-2: Possible recombination and emergence of potentially more virulent strains
This article has 13 authors:Reviewed by ScreenIT
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Modeling the Effect of Population-Wide Vaccination on the Evolution of COVID-19 Epidemic in Canada
This article has 3 authors:Reviewed by ScreenIT
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Validation of home oxygen saturations as a marker of clinical deterioration in patients with suspected COVID-19
This article has 6 authors:Reviewed by ScreenIT
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The Effect of Temperature on Covid-19 Confirmed Cases: Evidence from US Counties
This article has 4 authors:Reviewed by ScreenIT
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Modelling trachoma post-2020: opportunities for mitigating the impact of COVID-19 and accelerating progress towards elimination
This article has 10 authors:Reviewed by ScreenIT
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Self-organized stem cell-derived human lung buds with proximo-distal patterning and novel targets of SARS-CoV-2
This article has 6 authors:Reviewed by ScreenIT
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Population genetic analysis of Indian SARS-CoV-2 isolates reveals a unique phylogenetic cluster
This article has 2 authors:Reviewed by ScreenIT
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Modelling the impact of control measures against the COVID-19 pandemic in Viet Nam
This article has 5 authors:Reviewed by ScreenIT
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Prevalence and correlation of symptoms and comorbidities in COVID-19 patients: A systematic review and meta-analysis
This article has 10 authors:Reviewed by ScreenIT
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Ethnicity, household composition and COVID-19 mortality: a national linked data study
This article has 14 authors:Reviewed by ScreenIT