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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A causal inference approach for estimating effects of non-pharmaceutical interventions during Covid-19 pandemic
This article has 8 authors:Reviewed by ScreenIT
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Fine-scale variation in the effect of national border on COVID-19 spread: A case study of the Saxon-Czech border region
This article has 5 authors:Reviewed by ScreenIT
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The Serological Sciences Network (SeroNet) for COVID-19: Depth and Breadth of Serology Assays and Plans for Assay Harmonization
This article has 59 authors:Reviewed by ScreenIT
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Ammonium Sulfate Addition Reduces the Need for Guanidinium Isothiocyanate in the Denaturing Transport Medium Used for SARS-COV-2 RNA Detection
This article has 8 authors:Reviewed by ScreenIT
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Rapid Hypermutation B Cell Trajectory Recruits Previously Primed B Cells Upon Third SARS-Cov-2 mRNA Vaccination
This article has 12 authors:Reviewed by ScreenIT
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Flipped over U: structural basis for dsRNA cleavage by the SARS-CoV-2 endoribonuclease
This article has 7 authors:Reviewed by ScreenIT
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Development and validation of a quantitative instrument for measuring temporal and social disorientation in the Covid-19 crisis
This article has 5 authors:Reviewed by ScreenIT
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Longitudinal monitoring of SARS-CoV-2 neutralizing antibody titers and its impact on employee personal wellness decisions
This article has 14 authors:Reviewed by ScreenIT
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Convalescent plasma with a high level of virus-specific antibody effectively neutralizes SARS-CoV-2 variants of concern
This article has 34 authors:Reviewed by ScreenIT
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COVID-19 in Tunisia (North Africa): IgG and IgG subclass antibody responses to SARS-CoV-2 according to disease severity
This article has 26 authors:Reviewed by ScreenIT