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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Impact of the B.1.1.7 variant on neutralizing monoclonal antibodies recognizing diverse epitopes on SARS-CoV-2 Spike
This article has 27 authors:Reviewed by ScreenIT
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Mitigating aerosol infection risk in school buildings: the role of natural ventilation, volume, occupancy and CO2 monitoring
This article has 2 authors:Reviewed by ScreenIT
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A novel ACE2 isoform is expressed in human respiratory epithelia and is upregulated in response to interferons and RNA respiratory virus infection
This article has 27 authors:Reviewed by ScreenIT
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A monocyte/dendritic cell molecular signature of SARS-CoV-2-related multisystem inflammatory syndrome in children with severe myocarditis
This article has 50 authors:Reviewed by ScreenIT
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An Essential Role of UBXN3B in B Lymphopoiesis
This article has 14 authors:Reviewed by ScreenIT
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SARS-CoV-2 Antibodies Detected in Mother’s Milk Post-Vaccination
This article has 5 authors:Reviewed by ScreenIT
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COVID-associated pediatric hospitalization and ICU admission trends across a multi-state health system and the broader US population
This article has 6 authors:Reviewed by ScreenIT
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Single source of pangolin CoVs with a near identical Spike RBD to SARS-CoV-2
This article has 2 authors:Reviewed by ScreenIT
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Prohibit, Protect, or Adapt? The Changing Role of Volunteers in Palliative and Hospice Care Services During the COVID-19 Pandemic. A Multinational Survey (Covpall)
This article has 14 authors:Reviewed by ScreenIT
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High risk of patient self-inflicted lung injury in COVID-19 with frequently encountered spontaneous breathing patterns: a computational modelling study
This article has 10 authors:Reviewed by ScreenIT