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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Comprehensive analysis of disease pathology in immunocompetent and immunocompromised hamster models of SARS-CoV-2 infection
This article has 7 authors:Reviewed by ScreenIT
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Covariant Fitness Clusters Reveal Structural Evolution of SARS-CoV-2 Polymerase Across the Human Population
This article has 3 authors:Reviewed by ScreenIT
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Mild SARS-CoV-2 infection in rhesus macaques is associated with viral control prior to antigen-specific T cell responses in tissues
This article has 34 authors:Reviewed by ScreenIT
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Effectiveness of mRNA-1273 against SARS-CoV-2 Omicron and Delta variants
This article has 15 authors:Reviewed by ScreenIT
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Inpatient COVID-19 Mortality Rates: What are the predictors?
This article has 5 authors:Reviewed by ScreenIT
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Epidemiological waves - Types, drivers and modulators in the COVID-19 pandemic
This article has 10 authors:Reviewed by ScreenIT
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Consensus on COVID-19 Vaccination in Pediatric Oncohematological Patients, on Behalf of Infectious Working Group of Italian Association of Pediatric Hematology Oncology
This article has 37 authors:Reviewed by ScreenIT
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Estimation of Excess All-Cause Mortality Due to COVID-19 in Thailand
This article has 4 authors:Reviewed by ScreenIT
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VarLOCK: sequencing-independent, rapid detection of SARS-CoV-2 variants of concern for point-of-care testing, qPCR pipelines and national wastewater surveillance
This article has 18 authors:Reviewed by ScreenIT
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Engineering SARS-CoV-2 neutralizing antibodies for increased potency and reduced viral escape
This article has 23 authors:Reviewed by ScreenIT