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Record W3040238295 · doi:10.1093/jhered/esaa017

Genetic Melting Pot in Blacklegged Ticks at the Northern Edge of their Expansion Front

2020· article· en· W3040238295 on OpenAlexafffundabout
Benoit Talbot, Patrick A. Leighton, Manisha A. Kulkarni

Bibliographic record

VenueJournal of Heredity · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsUniversité de MontréalUniversity of Ottawa
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsIxodes scapularisBiologyTickBiological dispersalGenetic structureRange (aeronautics)Evolutionary biologyEcologyGenetic variationGeneticsPopulationIxodidaeDemography

Abstract

fetched live from OpenAlex

Blacklegged ticks (Ixodes scapularis) are considered to be the main vector of Lyme disease in eastern North America. They may parasitize a wide range of bird and mammal hosts. Northward dispersal of blacklegged ticks has been attributed largely to movement of hosts to areas outside of the current range of the tick, in conjunction with climate change. To better understand the drivers of range expansion in the blacklegged tick, we need investigations of the genetic connectivity and differentiation of tick populations at a fine spatial scale using appropriate markers. In this study, we investigated genetic connectivity and differentiation in blacklegged ticks, in an area of putatively recent advance in Ontario and Quebec, Canada, using microsatellite markers. Our findings suggest patchy differentiation of alleles, no spatial pattern of genetic structure, and genetic subdivision within sites, which are consistent with the very limited evidence available near the leading edge of range expansion of blacklegged ticks into Canada. These findings are consistent with the prevailing hypothesis, drawn from a variety of fields of study, suggesting that migratory birds from a variety of regions may be bringing hitchhiking ticks northward into Canada.

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 score0.348
Threshold uncertainty score0.632

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)0.0010.000

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 head0.015
GPT teacher head0.226
Teacher spread0.211 · 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

Citations3
Published2020
Admission routes3
Has abstractyes

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