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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Acute nasal dryness in COVID-19
This article has 8 authors:Reviewed by ScreenIT
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Modafinil for Wakefulness and Disorders of Consciousness in the Critical Care Units
This article has 3 authors:Reviewed by ScreenIT
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Distinct lung-homing receptor expression and activation profiles on NK cell and T cell subsets in COVID-19 and influenza
This article has 13 authors:Reviewed by ScreenIT
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Changes in inflammatory and immune drivers in response to immunomodulatory therapies in COVID-19
This article has 7 authors:Reviewed by ScreenIT
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Forecasting intensive care unit demand during the COVID-19 pandemic: A spatial age-structured microsimulation model
This article has 20 authors:Reviewed by ScreenIT
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Demographic Benchmarks for Equitable Coverage of COVID-19 Vaccination
This article has 5 authors:Reviewed by ScreenIT
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Assessing Age-Specific Vaccination Strategies and Post-vaccination Reopening Policies for COVID-19 Control Using SEIR Modeling Approach
This article has 3 authors:Reviewed by ScreenIT
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The E484K mutation in the SARS-CoV-2 spike protein reduces but does not abolish neutralizing activity of human convalescent and post-vaccination sera
This article has 10 authors:Reviewed by ScreenIT
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Impact of the COVID-19 pandemic on the mental health of Greek adults: a cross-sectional survey
This article has 5 authors:Reviewed by ScreenIT
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Natural variants in SARS-CoV-2 Spike protein pinpoint structural and functional hotspots with implications for prophylaxis and therapeutic strategies
This article has 4 authors:Reviewed by ScreenIT