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Record W2606565958 · doi:10.1139/cjz-2016-0134

Evidence for genetic hybridization between <i>Ixodes scapularis</i> and <i>Ixodes cookei</i>

2017· article· en· W2606565958 on OpenAlexaffvenueabout
James W. Patterson, Anna M. Duncan, Kelsey C. McIntyre, Vett K. Lloyd

Bibliographic record

VenueCanadian Journal of Zoology · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsMount Allison University
Fundersnot available
KeywordsIxodes scapularisBiologyBorrelia burgdorferiTickAmblyomma americanumZoologyEcologyGeneticsIxodidae

Abstract

fetched live from OpenAlex

Ixodes scapularis Say, 1821 (the black-legged tick) is becoming established in Canada. The northwards expansion of I. scapularis leads to contact between I. scapularis and Ixodes cookei Packard, 1869, a well-established tick species in Eastern Canada. Examination of I. cookei and I. scapularis collected from New Brunswick revealed ticks with ambiguous morphologies, with either a mixture or intermediate traits typical of I. scapularis and I. cookei, including in characteristics typically used as species identifiers. Genetic analysis to determine if these ticks represent hybrids revealed that four had I. cookei derived mitochondrial DNA but I. scapularis nuclear DNA. In one case, the nuclear sequence showed evidence of heterozygosity for I. scapularis and I. cookei sequences, whereas in the others, the nuclear DNA appeared to be entirely derived from I. scapularis. These data strongly suggest genetic hybridization between these two species. Ixodes cookei and hybrid ticks were readily collected from humans and companion animals and specimens infected with Borrelia burgdorferi Johnson et al., 1984, the causative agent of Lyme disease, were identified. These findings raise the issue of genetic introgression of I. scapularis genes into I. cookei and warrant reassessment of the capacity of I. cookei and I. cookei × I. scapularis hybrids to vector Borrelia infection.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.039
GPT teacher head0.274
Teacher spread0.235 · 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

Citations24
Published2017
Admission routes3
Has abstractyes

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