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Record W2043777111 · doi:10.7589/0090-3558-46.1.297

Identification of Parelaphostrongylus odocoilei (Nematoda: Protostrongylidae) First-Stage Larvae in the Feces of Gray Wolves (Canis lupus) by Molecular Methods

2010· article· en· W2043777111 on OpenAlexaffabout
Heather M. Bryan, Kathrin A. Sim, Chris T. Darimont, Paul C. Paquet, Brent Wagner, Violeta Muñoz‐Fuentes, Judit E. G. Smits, Neil B. Chilton

Bibliographic record

VenueJournal of Wildlife Diseases · 2010
Typearticle
Languageen
FieldVeterinary
TopicHelminth infection and control
Canadian institutionsRaincoast Conservation FoundationUniversity of CalgaryUniversity of Saskatchewan
Fundersnot available
KeywordsBiologyFecesSingle-strand conformation polymorphismCanisOdocoileusZoologyRibosomal DNAVeterinary medicinePolymerase chain reactionMicrobiologyGeneticsEcologyPhylogenetics

Abstract

fetched live from OpenAlex

First-stage nematode larvae with a dorsal-spine (DSL) were detected in five of 1,565 fecal samples from gray wolves (Canis lupus) collected in British Columbia, Canada, between 2005 and 2008. Molecular techniques were used to identify the DSL because it was not possible to determine their species identity using morphologic characters. The DSL were identified as Parelaphostrongylus odocoilei based on the results of single-strand conformation polymorphism (SSCP) analyses and DNA sequencing of the ribosomal DNA first and second internal transcribed spacers. Finding DSL of P. odocoilei in the feces of gray wolves was unexpected because P. odocoilei adults are parasites of cervids and bovids. The most likely explanation for the presence of DSL in wolf feces is that they were ingested along with the viscera of recently consumed prey. This was probably black-tailed deer (Odocoileus hemionus columbianus), which are known in the sampling area to be hosts of P. odocoilei. The present study demonstrates the use of SSCP and DNA sequencing for the identification, to the species level, of parasitic nematode larvae in feces.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.329
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.016
GPT teacher head0.341
Teacher spread0.325 · 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

Citations10
Published2010
Admission routes2
Has abstractyes

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