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Record W2150002753 · doi:10.1603/me13067

Ticks (Acari: Ixodidae) on Small Mammals in Kootenay National Park, British Columbia, Canada

2013· article· en· W2150002753 on OpenAlexaffabout
Clare A. Anstead, Yeen Ten Hwang, Neil B. Chilton

Bibliographic record

VenueJournal of Medical Entomology · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsMinistry of the Environment, Conservation and ParksSaskatchewan Ministry of AgricultureUniversity of Saskatchewan
Fundersnot available
KeywordsBiologyIxodidaeAcariNational parkZoologyNymphEcology

Abstract

fetched live from OpenAlex

Two hundred and ninety-one ticks (i.e., 185 larvae, 72 nymphs, and 34 adults) were removed from 153 small mammals comprising six species collected in Verdant Forest, Numa Forest, and Marble Canyon within Kootenay National Park, British Columbia, Canada. Morphological examination and molecular analyses (i.e., polymerase chain reaction-single-strand conformation polymorphism [PCR-SSCP] and DNA sequencing of the mitochondrial 16S rRNA gene) of the ticks revealed that most individuals were Ixodes angustus Neumann. All life cycle stages of I. angustus were found primarily on southern red-backed voles, Clethrionomys gapperi (Vigors). Two Dermacentor andersoni Stiles females were also found on these small mammals. The results of the molecular analyses also revealed that there were three 16S haplotypes of I. angustus and two 16S haplotypes of D. andersoni. A comparison of available sequence data suggests genetic divergence between I. angustus near the western and eastern limits of the species distributional range in North America. Additional studies are needed to determine whether there are genetic differences between I. angustus from North America, Japan, and Russia, and whether there is geographical variation in the ability of ticks to transmit pathogens to their mammalian hosts.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.495
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0180.000

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 head0.010
GPT teacher head0.227
Teacher spread0.218 · 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.

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

Citations9
Published2013
Admission routes2
Has abstractyes

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