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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In vitro effect of a non-immunosuppressive FKBP ligand, FK1706, on SARS-CoV-2 replication in combination with antivirals
This article has 4 authors:Reviewed by ScreenIT
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Chronic Disease and Workforce Participation Among Medicaid Enrollees Over 50: The Potential Impact of Medicaid Work Requirements Post-COVID-19
This article has 5 authors:Reviewed by ScreenIT
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Machine learning-based approach KEVOLVE efficiently identifies SARS-CoV-2 variant-specific genomic signatures
This article has 5 authors:Reviewed by ScreenIT
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Heterologous ChAdOx1-BNT162b2 vaccination in Korean cohort induces robust immune and antibody responses that includes Omicron
This article has 9 authors:Reviewed by ScreenIT
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Safety and Non-Inferiority Evaluation of Two Immunization Schedules with an Inactivated SARS-CoV-2 Vaccine in Adults: A Randomized Clinical Trial
This article has 31 authors:Reviewed by ScreenIT
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Duration of protection of BNT162b2 and mRNA-1273 COVID-19 vaccines against symptomatic SARS-CoV-2 Omicron infection in Qatar
This article has 24 authors:Reviewed by ScreenIT
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Time to reinfection and vaccine breakthrough SARS-CoV-2 infections: a retrospective cohort study
This article has 6 authors:Reviewed by ScreenIT
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COVID-19 excess deaths in Eastern European countries associated with weaker regulation implementation and lower vaccination coverage
This article has 4 authors:Reviewed by ScreenIT
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Suite of TMPRSS2 Assays for Screening Drug Repurposing Candidates as Potential Treatments of COVID-19
This article has 17 authors:Reviewed by ScreenIT
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Protection of COVID-19 vaccination and previous infection against Omicron BA.1, BA.2 and Delta SARS-CoV-2 infections
This article has 13 authors:Reviewed by ScreenIT