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Record W3000395518 · doi:10.3390/v12010115

Population- and Variant-Based Genome Analyses of Viruses from Vaccine-Derived Rabies Cases Demonstrate Product Specific Clusters and Unique Patterns

2020· article· en· W3000395518 on OpenAlexaffabout
Sten Calvelage, Marcin Smreczak, Anna Orłowska, Conrad M. Freuling, Thomas Müller, Christine Fehlner‐Gardiner, Susan A. Nadin‐Davis, Dirk W. Höper, Paweł Trębas

Bibliographic record

VenueViruses · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicRabies epidemiology and control
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsRabiesRabies virusVirologyBiologyRabies vaccinePopulationGenetic diversityVaccinationLyssavirusRhabdoviridaeMedicineEnvironmental health

Abstract

fetched live from OpenAlex

Rabies in wildlife has been successfully controlled in parts of Europe and North America using oral rabies vaccination, i.e., the distribution of baits containing live-attenuated virus strains. Occasionally, these vaccines caused vaccine virus-induced rabies cases. To elucidate the mechanisms of genetic selection and the effect of viral populations on these rabies cases, a next generation sequencing approach as well as comprehensive data analyses of the genetic diversity of Street Alabama Dufferin (SAD) and ERA vaccine virus strains and vaccine-induced rabies cases from Canada and several European countries were conducted. As a result, twelve newly generated sets of sequencing data from Canada and Poland were added to a pool of previously investigated samples. While the population-based analysis showed a segregation of viruses of ERA vaccine-induced rabies cases from those of SAD Bern original (SAD Bernorig)-derived rabies cases, the in-depth variant analysis revealed three distinct combinations of selected variants for the ERA vaccine-induced cases, suggesting the presence of multiple replication-competent haplotypes in the investigated ERA-BHK21 vaccine. Our findings demonstrate the potential of a deep sequencing approach in combination with comprehensive analyses on the consensus, population, and variant level.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.432
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.293
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2020
Admission routes2
Has abstractyes

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