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-positive patients display considerable differences in proteome diversity in urine, nasopharyngeal, gargle solution and bronchoalveolar lavage fluid samples
This article has 5 authors:Reviewed by ScreenIT
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Quantifying behavior change during the first year of the COVID-19 pandemic in the United States
This article has 5 authors:Reviewed by ScreenIT
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Durability and Cross-Reactivity of SARS-CoV-2 mRNA Vaccine in Adolescent Children
This article has 14 authors:Reviewed by ScreenIT
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Identifying SARS-CoV-2 regional introductions and transmission clusters in real time
This article has 5 authors:Reviewed by ScreenIT
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Reconstruction of transmission chains of SARS-CoV-2 amidst multiple outbreaks in a geriatric acute-care hospital: a combined retrospective epidemiological and genomic study
This article has 15 authors:This article has been curated by 1 group: -
Comparison of SARS-CoV-2 Reverse Transcriptase Polymerase Chain Reaction and BinaxNOW Rapid Antigen Tests at a Community Site During an Omicron Surge
This article has 21 authors:Reviewed by ScreenIT
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Omicron Impact in India: Analysis of the Ongoing COVID-19 Third Wave Based on Global Data
This article has 1 author:Reviewed by ScreenIT
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Prevalence of saliva immunoglobulin A antibodies reactive with severe acute respiratory syndrome coronavirus 2 among Japanese people unexposed to the virus
This article has 20 authors:Reviewed by ScreenIT
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Modelling COVID-19 vaccine breakthrough infections in highly vaccinated Israel—The effects of waning immunity and third vaccination dose
This article has 4 authors:Reviewed by ScreenIT
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A Method for Variant Agnostic Detection of SARS-CoV-2, Rapid Monitoring of Circulating Variants, and Early Detection of Emergent Variants Such as Omicron
This article has 26 authors:Reviewed by ScreenIT