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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Clinical diagnosis of 8274 samples with 2019-novel coronavirus in Wuhan
This article has 24 authors:Reviewed by ScreenIT
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Estimating the daily trend in the size of the COVID-19 infected population in Wuhan
This article has 3 authors:Reviewed by ScreenIT
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Assessing the effects of metropolitan-wide quarantine on the spread of COVID-19 in public space and households
This article has 8 authors:Reviewed by ScreenIT
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Ophthalmologic evidence against the interpersonal transmission of 2019 novel coronavirus through conjunctiva
This article has 4 authors:Reviewed by ScreenIT
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Neutrophil-to-lymphocyte ratio predicts critical illness patients with 2019 coronavirus disease in the early stage
This article has 22 authors:Reviewed by ScreenIT
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Beyond R 0 : heterogeneity in secondary infections and probabilistic epidemic forecasting
This article has 4 authors:Reviewed by ScreenIT
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Laboratory Diagnosis and Monitoring the Viral Shedding of SARS-CoV-2 Infection
This article has 21 authors:Reviewed by ScreenIT
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Facemask shortage and the novel coronavirus disease (COVID-19) outbreak: Reflections on public health measures
This article has 5 authors:Reviewed by ScreenIT
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The immune vulnerability landscape of the 2019 Novel Coronavirus, SARS-CoV-2
This article has 17 authors:Reviewed by ScreenIT
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Primary Care Practitioners’ Response to 2019 Novel Coronavirus Outbreak in China
This article has 4 authors:Reviewed by ScreenIT