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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Modeling and prediction of the 2019 coronavirus disease spreading in China incorporating human migration data
This article has 5 authors:Reviewed by ScreenIT
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Prediction of the Epidemic of COVID-19 Based on Quarantined Surveillance in China
This article has 7 authors:Reviewed by ScreenIT
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The effectiveness of full and partial travel bans against COVID-19 spread in Australia for travellers from China during and after the epidemic peak in China
This article has 3 authors:Reviewed by ScreenIT
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Quantifying the risk of indoor drainage system in multi-unit apartment building as a transmission route of SARS-CoV-2
This article has 6 authors:Reviewed by ScreenIT
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Population-level COVID-19 mortality risk for non-elderly individuals overall and for non-elderly individuals without underlying diseases in pandemic epicenters
This article has 3 authors:Reviewed by ScreenIT
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Suitability of two rapid lateral flow immunochromatographic assays for predicting SARS‐CoV‐2 neutralizing activity of sera
This article has 15 authors:Reviewed by ScreenIT
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Optimal control of an SIR epidemic through finite-time non-pharmaceutical intervention
This article has 1 author:Reviewed by ScreenIT
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The association between mechanical ventilator compatible bed occupancy and mortality risk in intensive care patients with COVID-19: a national retrospective cohort study
This article has 11 authors:Reviewed by ScreenIT
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Assessment of a COVID-19 Control Plan on an Urban University Campus During a Second Wave of the Pandemic
This article has 27 authors:Reviewed by ScreenIT
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Quantification of SARS-CoV-2 viral copy number in saliva mouthwash samples using digital droplet PCR
This article has 5 authors:Reviewed by ScreenIT