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Record W2102610488 · doi:10.7589/0090-3558-43.3.432

FEASIBILITY OF USING COYOTES (CANIS LATRANS) AS SENTINELS FOR BOVINE MYCOBACTERIOSIS (MYCOBACTERIUM BOVIS) INFECTION IN WILD CERVIDS IN AND AROUND RIDING MOUNTAIN NATIONAL PARK, MANITOBA, CANADA

2007· article· en· W2102610488 on OpenAlexaffabout
Cheryl Sangster, Doug Bergeson, Cyril Lutze-Wallace, Vince Crichton, Gary A. Wobeser

Bibliographic record

VenueJournal of Wildlife Diseases · 2007
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsCanadian Food Inspection AgencyParks CanadaUniversity of Saskatchewan
Fundersnot available
KeywordsOdocoileusCanisMycobacterium bovisBiologyVeterinary medicineNational parkMycobacteriumLivestockParatuberculosisPolymerase chain reactionZoologyEcologyPathologyTuberculosisMedicineBacteria

Abstract

fetched live from OpenAlex

Elk (Cervus elaphus manitobensis) and white-tailed deer (Odocoileus virginianus) in the Riding Mountain National Park (RMNP) region of southwestern Manitoba have been identified as a likely wildlife reservoir of Mycobacterium bovis, the causative agent of bovine mycobacteriosis in livestock. The feasibility of using coyotes (Canis latrans) collected from trappers as a sentinel species was investigated. Retropharyngeal, mesenteric, and colonic lymph nodes and tonsils collected at necropsy from 82 coyotes were examined by bacterial culture, polymerase chain reaction (PCR), and acid-fast histopathology. Mycobacterium bovis was not identified in any animal by culture or PCR although Mycobacterium avium species were isolated. A single acid-fast organism was identified on histopathologic examination of one animal. Based on the methods used in this study, trapper-caught coyotes do not appear to be a sensitive sentinel species of M. bovis infection in cervids in and around RMNP.

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)0.002
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 score0.031
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.042
GPT teacher head0.331
Teacher spread0.289 · 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

Citations16
Published2007
Admission routes2
Has abstractyes

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