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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An interpretable mortality prediction model for COVID-19 patients
This article has 30 authors:Reviewed by ScreenIT
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Evaluation of Enzyme-Linked Immunoassay and Colloidal Gold-Immunochromatographic Assay Kit for Detection of Novel Coronavirus (SARS-Cov-2) Causing an Outbreak of Pneumonia (COVID-19)
This article has 7 authors:Reviewed by ScreenIT
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Potential therapeutic effects of dipyridamole in the severely ill patients with COVID-19
This article has 25 authors:Reviewed by ScreenIT
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Sex differences in clinical findings among patients with coronavirus disease 2019 (COVID-19) and severe condition
This article has 11 authors:Reviewed by ScreenIT
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Heart injury signs are associated with higher and earlier mortality in coronavirus disease 2019 (COVID-19)
This article has 19 authors:Reviewed by ScreenIT
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Infection Dynamics of Coronavirus Disease 2019 (Covid-19) Modeled with the Integration of the Eyring’s Rate Process Theory and Free Volume Concept
This article has 1 author:Reviewed by ScreenIT
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Estimate the incubation period of coronavirus 2019 (COVID-19)
This article has 9 authors:Reviewed by ScreenIT
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Clinical characteristics of 36 non-survivors with COVID-19 in Wuhan, China
This article has 4 authors:Reviewed by ScreenIT
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Modeling the epidemic dynamics and control of COVID‐19 outbreak in China
This article has 2 authors:Reviewed by ScreenIT
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Evaluation of the clinical characteristics of suspected or confirmed cases of COVID-19 during home care with isolation: A new retrospective analysis based on O2O
This article has 9 authors:Reviewed by ScreenIT