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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COVID-19 Mortality Following Mass Gatherings
This article has 4 authors:Reviewed by ScreenIT
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The Lebanese COVID-19 Cohort; A Challenge for the ABO Blood Group System
This article has 3 authors:Reviewed by ScreenIT
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Mathematical Analysis of COVID-19 Transmission Dynamics with a Case Study of Nigeria and its Computer Simulation
This article has 4 authors:Reviewed by ScreenIT
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Extensive Genetic Diversity and Host Range of Rodent-borne Coronaviruses
This article has 7 authors:Reviewed by ScreenIT
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Typhoon eye effect versus ripple effect: the role of family size on mental health during the COVID-19 pandemic in Pakistan
This article has 7 authors:Reviewed by ScreenIT
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Effectiveness of interventions targeting air travellers for delaying local outbreaks of SARS-CoV-2
This article has 8 authors:Reviewed by ScreenIT
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Association between work situation and life satisfaction during the COVID-19 pandemic: prospective cohort study in Norway
This article has 6 authors:Reviewed by ScreenIT
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Impact of the COVID-19 pandemic on ongoing health research: an ad hoc survey among investigators in Germany
This article has 7 authors:Reviewed by ScreenIT
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The impact of super-spreader cities, highways, and intensive care availability in the early stages of the COVID-19 epidemic in Brazil
This article has 4 authors:Reviewed by ScreenIT
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Emergence of the First Strains of SARS-CoV-2 Lineage B.1.1.7 in Romania: Genomic Analysis
This article has 5 authors:Reviewed by ScreenIT