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 sequencing reveals rapid transmission from college student clusters resulting in morbidity and deaths in vulnerable populations
This article has 5 authors: -
How to Flatten the post-lockdown epidemic trajectory
This article has 2 authors:Reviewed by ScreenIT
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Forecasting and modeling of the COVID-19 pandemic in the USA with a timed intervention model
This article has 3 authors:Reviewed by ScreenIT
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Using Feedback on Symptomatic Infections to Contain the Coronavirus Epidemic: Insight from a SPIR Model
This article has 1 author:Reviewed by ScreenIT
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Risk Analysis of COVID‐19 Infections in Kolkata Metropolitan City: A GIS‐Based Study and Policy Implications
This article has 4 authors:Reviewed by ScreenIT
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Variation in SARS-CoV-2 outbreaks across sub-Saharan Africa
This article has 17 authors:Reviewed by ScreenIT
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A systematic review of droplet and aerosol generation in dentistry
This article has 10 authors:Reviewed by ScreenIT
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Electrostatic filters to reduce COVID-19 spread in bubble CPAP: an in vitro study of safety and efficacy
This article has 4 authors:Reviewed by ScreenIT
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COVID-19 Utilization and Resource Visualization Engine (CURVE) to Forecast In-Hospital Resources
This article has 10 authors:Reviewed by ScreenIT
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Social Determinants Associated with COVID-19 Mortality in the United States
This article has 8 authors:Reviewed by ScreenIT