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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SARS-CoV-2 antibody persistence after five and twelve months: A cohort study from South-Eastern Norway
This article has 14 authors:Reviewed by ScreenIT
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Wastewater surveillance using ddPCR reveals highly accurate tracking of Omicron variant due to altered N1 probe binding efficiency
This article has 5 authors:Reviewed by ScreenIT
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Insights on Telemedicine Use by Physiatrists Before, During, and Beyond the COVID-19 Pandemic
This article has 4 authors:Reviewed by ScreenIT
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COVID-19 Surveillance in the Biobank at the Colorado Center for Personalized Medicine: Observational Study
This article has 8 authors:Reviewed by ScreenIT
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Closing the health inequity gap during the pandemic: COVID-19 mortality among racial and ethnic groups in Connecticut, March 2020 to December 2021
This article has 6 authors:Reviewed by ScreenIT
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Neural dysregulation in post-COVID fatigue
This article has 7 authors:Reviewed by ScreenIT
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Post-COVID-19 tele-survey for persistent symptoms in a single center hospital cohort in India along with a parallel country-wide web-survey
This article has 12 authors:Reviewed by ScreenIT
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Immunity post-COVID-19 recovery boosts the antibody immune response to SARS-CoV-2 vaccination
This article has 20 authors:Reviewed by ScreenIT
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Genomic monitoring unveils a high prevalence of SARS-CoV-2 Omicron variant in vaccine breakthrough cases
This article has 6 authors:Reviewed by ScreenIT
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Influenza vaccination reveals sex dimorphic imprints of prior mild COVID-19
This article has 36 authors:Reviewed by ScreenIT