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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The First GAEN-Based COVID-19 Contact Tracing App in Norway Identifies 80% of Close Contacts in “Real Life” Scenarios
This article has 9 authors:Reviewed by ScreenIT
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Age-dependent association between SARS-CoV-2 cases reported by passive surveillance and viral load in wastewater
This article has 3 authors:Reviewed by ScreenIT
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The BNT162b2 mRNA Covid-19 vaccine does not impair sperm parameters
This article has 6 authors:Reviewed by ScreenIT
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The Role of Host Cell Glycans on Virus Infectivity: The SARS‐CoV‐2 Case
This article has 3 authors:Reviewed by ScreenIT
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Within-host evolution of SARS-CoV-2 in an immunosuppressed COVID-19 patient as a source of immune escape variants
This article has 23 authors:Reviewed by ScreenIT
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Immune profile of children with post-acute sequelae of SARS-CoV-2 infection (Long Covid)
This article has 7 authors:Reviewed by ScreenIT
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Structure-based design of a highly stable, covalently-linked SARS-CoV-2 spike trimer with improved structural properties and immunogenicity
This article has 19 authors:Reviewed by ScreenIT
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Modeling and Predicting Antibody Durability for mRNA-1273 Vaccine for SARS-CoV-2 Variants
This article has 3 authors:Reviewed by ScreenIT
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Characterization of the emerging B.1.621 variant of interest of SARS-CoV-2
This article has 21 authors:Reviewed by ScreenIT
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Use of US Blood Donors for National Serosurveillance of Severe Acute Respiratory Syndrome Coronavirus 2 Antibodies: Basis for an Expanded National Donor Serosurveillance Program
This article has 46 authors:Reviewed by ScreenIT