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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Multinational modeling of SARS-CoV-2 spreading dynamics: Insights on the heterogeneity of COVID-19 transmission and its potential healthcare burden
This article has 4 authors:Reviewed by ScreenIT
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Applying the SEIR Model in Forecasting The COVID-19 Trend in Malaysia: A Preliminary Study
This article has 2 authors:Reviewed by ScreenIT
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Nosocomial infections among patients with COVID-19, SARS and MERS: a rapid review and meta-analysis
This article has 21 authors:Reviewed by ScreenIT
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Effects of temperature and humidity on the spread of COVID-19: A systematic review
This article has 4 authors:Reviewed by ScreenIT
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Population anxiety and positive behaviour change during the COVID‐19 epidemic: Cross‐sectional surveys in Singapore, China and Italy
This article has 9 authors:Reviewed by ScreenIT
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Clinical academic research in the time of Corona: A simulation study in England and a call for action
This article has 12 authors:Reviewed by ScreenIT
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Coronavirus PPE: a positive pressure hood assembled from ubiquitous, low-cost materials
This article has 1 author:Reviewed by ScreenIT
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Supportive care for patient with respiratory diseases: an umbrella review
This article has 18 authors:Reviewed by ScreenIT
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Forecasting Hospital Staff Availability During The COVID-19 Epidemic
This article has 4 authors:Reviewed by ScreenIT
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The Longevity-Frailty Hypothesis: Evidence from COVID-19 Death Rates in Europe
This article has 3 authors:Reviewed by ScreenIT