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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The Mean Unfulfilled Lifespan (MUL): A new indicator of the impact of mortality shocks on the individual lifespan, with application to mortality reversals induced by COVID-19
This article has 1 author:Reviewed by ScreenIT
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Survey of peridomestic mammal susceptibility to SARS-CoV-2 infection
This article has 12 authors: -
Post-lockdown Dynamics of COVID-19 in New York, Florida, Arizona, and Wisconsin
This article has 3 authors:Reviewed by ScreenIT
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Significance of SARS-CoV-2 specific antibody testing during COVID-19 vaccine allocation
This article has 3 authors:Reviewed by ScreenIT
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Household transmission of COVID-19, Shenzhen, January-February 2020
This article has 14 authors:Reviewed by ScreenIT
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On the sensitivity of non-pharmaceutical intervention models for SARS-CoV-2 spread estimation
This article has 13 authors:Reviewed by ScreenIT
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Remarks on pooling Coronavirus tests
This article has 2 authors:Reviewed by ScreenIT
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How did governmental interventions affect the spread of COVID-19 in European countries?
This article has 4 authors:Reviewed by ScreenIT
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The impact of public health interventions in the Nordic countries during the first year of SARS-CoV-2 transmission and evolution
This article has 6 authors:Reviewed by ScreenIT
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Assessment of the knowledge, preferences and concern regarding the prospective COVID-19 vaccine among adults residing in New Delhi, India – A cross-sectional study
This article has 9 authors:Reviewed by ScreenIT