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Record W4411155878 · doi:10.1139/cjz-2025-0011

Morphological diversity of two phylogeographic lineages of Arctic grayling (<i>Thymallus arcticus</i>) in Alberta

2025· article· en· W4411155878 on OpenAlexaffvenueabout
Jessica R. Reilly, Laura MacPherson, Sara A. Bumstead, Kristy M. Wakeling, James K. Bull, Joshua M. Miller

Bibliographic record

VenueCanadian Journal of Zoology · 2025
Typearticle
Languageen
FieldMathematics
TopicMorphological variations and asymmetry
Canadian institutionsMacEwan UniversityGovernment of Alberta
Fundersnot available
KeywordsGraylingBiologyPhylogeographyArcticEcologyDiversity (politics)ZoologyPhylogenetics

Abstract

fetched live from OpenAlex

Biodiversity is declining globally, necessitating conservation strategies that protect genetic and phenotypic diversity within species. In North America, Arctic grayling ( Thymallus arcticus (Pallas, 1776)) exhibit substantial mitochondrial DNA divergence corresponding to two phylogeographic lineages termed Nahanni and Beringia. However, phenotypic variation has not been widely explored and there has been no direct comparison between the two lineages. This study examined morphological variation between these lineages in Alberta and whether observed variability was associated with sex. Morphology of T. arcticus was investigated using two approaches after assigning fish to a lineage based on their mitochondrial DNA haplotype. Geometric morphometric techniques were used to assess body shape differences between the two lineages and sex considering 16 two-dimensional landmarks. Twelve meristic characters were also enumerated and compared. Subtle yet significant differences in body shape and three meristic traits (lateral line scales, branched pelvic rays, and pyloric caeca) were identified, with body shape analysis resulting in 95% accuracy in lineage assignment. Body shape was also influenced by sex, corroborating evidence of sexual dimorphism in T. arcticus. These results support potential classification of the lineages as evolutionary significant units worthy of independent protection.

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 score0.166
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.026
GPT teacher head0.269
Teacher spread0.242 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

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