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Record W1979937051 · doi:10.1017/s0031182012001758

Cryptic<i>Onchocerca</i>species infecting North American cervids, with implications for the evolutionary history of host associations in<i>Onchocerca</i>

2012· article· en· W1979937051 on OpenAlexaffabout
Quinn S. McFrederick, Tamara S. Haselkorn, Guilherme G. Verocai, John Jaenike

Bibliographic record

VenueParasitology · 2012
Typearticle
Languageen
FieldMedicine
TopicParasitic Diseases Research and Treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBiologyOnchocercaOnchocerciasisPhylogenetic treeHost (biology)ZoologyPhylogeneticsEvolutionary biologyEcologyGeneticsOnchocerca volvulusGeneImmunology

Abstract

fetched live from OpenAlex

Parasites in the genus Onchocerca infect humans, ruminants, camels, horses, suids, and canids, with effects ranging from relatively benign to debilitating. In North America, Onchocerca cervipedis is the sole species known to infect cervids, while at least 5 Onchocerca species infect Eurasian cervids. In this study, we report the discovery of a cervid-parasitizing Onchocerca only distantly related to O. cervipedis. To reconstruct the phylogenetic history of the genus Onchocerca, we used newly acquired DNA sequence from O. cervipedis (from moose in Northwest Territories, Canada) and from the newly discovered species (from white-tailed deer in upstate New York), as well as previously published sequences. Ancestral host reconstructions suggest that host switches have been common throughout the evolutionary history of Onchocerca, and that bovid- and cervid-parasitizing species have been particularly important sources of descendant species. North America cervids might therefore serve as a source for Onchocerca invasions into new hosts. Given the high density of deer populations, the potential for zoonotic infections may also exist. Our discovery of a new Onchocerca species with relatively limited sampling suggests that the diversity of Onchocerca associated with cervids in North America may be greater than previously thought, and surveys utilizing molecules and morphology are necessary.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.040
GPT teacher head0.346
Teacher spread0.305 · 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

Citations21
Published2012
Admission routes2
Has abstractyes

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