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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Hippo signaling pathway activation during SARS-CoV-2 infection contributes to host antiviral response
This article has 17 authors:Reviewed by ScreenIT
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Built environment’s impact on COVID-19 transmission and mental health revealed by COVID-19 Participant Experience data from the All of Us Research Program
This article has 6 authors:Reviewed by ScreenIT
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Early SARS-CoV-2 Reinfections within 60 Days and Implications for Retesting Policies
This article has 11 authors:Reviewed by ScreenIT
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Combined Infection Control Interventions Protect the Essential Workforce from Occupationally-Acquired SARS-CoV-2 during Produce Production, Harvesting and Processing Activities
This article has 9 authors:Reviewed by ScreenIT
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Vaccine Effectiveness of BNT162b2 Against Delta and Omicron Variants in Adolescents
This article has 5 authors:Reviewed by ScreenIT
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Use of face masks did not impact COVID-19 incidence among 10–12-year-olds in Finland
This article has 4 authors:Reviewed by ScreenIT
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Distinct evolutionary trajectories of SARS-CoV-2-interacting proteins in bats and primates identify important host determinants of COVID-19
This article has 9 authors:Reviewed by ScreenIT
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Summaries, Analysis and Simulations of Recent COVID-19 Epidemics in Mainland China
This article has 1 author:Reviewed by ScreenIT
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Have Deaths of Despair Risen during the COVID-19 Pandemic? A Systematic Review
This article has 4 authors:Reviewed by ScreenIT
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Impact of the COVID-19 epidemic on mortality in rural coastal Kenya
This article has 25 authors:Reviewed by ScreenIT