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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Isolation of SARS-CoV-2 from the air in a car driven by a COVID patient with mild illness
This article has 7 authors:Reviewed by ScreenIT
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Modeling coupling dynamics between the transmission, intervention of COVID-19 and economic development
This article has 4 authors:Reviewed by ScreenIT
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Is Blood Type Associated with COVID-19 Severity?
This article has 4 authors:Reviewed by ScreenIT
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Alternative Approaches for Modelling COVID-19: High-Accuracy Low-Data Predictions
This article has 7 authors:Reviewed by ScreenIT
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Comprehensive analysis of the host-virus interactome of SARS-CoV-2
This article has 10 authors:Reviewed by ScreenIT
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Test-trace-isolate-quarantine (TTIQ) intervention strategies after symptomatic COVID-19 case identification
This article has 3 authors:Reviewed by ScreenIT
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Stochastic model for COVID-19 in slums: interaction between biology and public policies
This article has 2 authors:Reviewed by ScreenIT
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Comparing the impact of vaccination strategies on the spread of COVID-19, including a novel household-targeted vaccination strategy
This article has 3 authors:Reviewed by ScreenIT
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Fitting to the UK COVID-19 outbreak, short-term forecasts and estimating the reproductive number
This article has 8 authors:Reviewed by ScreenIT
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The COVID-19 Consequences of College Class Continuity Calculator: A Tool to Provide Students and Administrators with Estimated Risks of Returning to Campus
This article has 4 authors:Reviewed by ScreenIT