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Record W2773237334 · doi:10.1155/2017/2978718

Tracking the Origin and Deciphering the Phylogenetic Relationship of Porcine Epidemic Diarrhea Virus in Ecuador

2017· article· en· W2773237334 on OpenAlexaffabout
Maritza Barrera, Ana Garrido, María S. Vaca, Danilo Granda, Alfredo Acosta, Lester J. Pérez

Bibliographic record

VenueBioMed Research International · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsSaint John Regional Hospital
FundersCollege of Veterinary Medicine, University of MinnesotaSecretaría de Educación Superior, Ciencia, Tecnología e InnovaciónUniversity of Minnesota
KeywordsPorcine epidemic diarrhea virusPhylogenetic treeCladeBiologyVirologyGenBankOutbreakPhylogeneticsPhylogeographyMolecular epidemiologyVirusGeneGeneticsGenotype

Abstract

fetched live from OpenAlex

In 2010, new Chinese strains of porcine epidemic diarrhea virus (PEDV), clinically more severe than the classical strains, emerged. These strains were spread to United States in 2013 through an intercontinental transmission from China with further spreading across the world, evidencing the emergent nature of these strains. In the present study, an analysis of PEDV field sequences from Ecuador was conducted by comparing all the PEDV S gene sequences available in the GenBank database. Phylogenetic comparisons and Bayesian phylogeographic inference based on complete S gene sequences were also conducted to track the origin and putative route of PEDV. The sequence from the PED-outbreak in Ecuador was grouped into the clade II of PEDV genogroup 2a together with other sequences of isolates from Mexico, Canada, and United States. The phylogeographic study revealed the emergence of the Chinese PEDV strains, followed by spreading to US in 2013, from US to Korea, and later the introduction of PEDV to Canada, Mexico, and Ecuador directly from the US. The sources of imports of live swine in Ecuador in 2014 were mainly from Chile and US. Thus, this movement of pigs is suggested as the main way for introducing PEDV to Ecuador.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.241
GPT teacher head0.412
Teacher spread0.171 · 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

Citations14
Published2017
Admission routes2
Has abstractyes

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