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Record W1539532915 · doi:10.1111/bij.12398

Polymorphism in lake trout in Great Bear Lake: intra-lake morphological diversification at two spatial scales

2014· article· en· W1539532915 on OpenAlexaff
Louise Chavarie, Katie E. Howland, Les N. Harris, William M. Tonn

Bibliographic record

VenueBiological Journal of the Linnean Society · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans CanadaUniversity of Alberta
Fundersnot available
KeywordsTroutIntraspecific competitionBiologySalvelinusEcologyHabitatSalmonidaeSpatial ecologySpatial variabilityZoologyFish <Actinopterygii>FisheryRainbow trout

Abstract

fetched live from OpenAlex

Great Bear Lake is the most northerly lake of its size and provides unique opportunities for intraspecific diversification. Despite increasing attention to intraspecific polymorphism, several knowledge gaps remain (e.g. determining the extent of intraspecific diversification in large relatively pristine lakes and at which spatial scale it can occur). We focused on geographical patterns of morphological differentiation within lake trout (Salvelinus namaycush) to describe two levels of intralake diversification in Great Bear Lake. We used a combination of geometric and traditional linear measurements to quantify differences in body shape, head shape, and fin and body lengths among 910 adult lake trout from the five distinct arms of Great Bear Lake. Although head and fin linear measurements discriminated the three common morphotypes at the whole-lake level, inter-arm variation in body shape was observed within each morphotype. A comparison of genetic and morphological distance matrices revealed the lack of an association between the two sets of data, although both comparisons revealed an association in the inter-arm variation patterns among morphotypes, suggesting a phenotypically plastic response to distinct environments. The whole-lake and inter-arm morphological variation observed within lake trout demonstrates the importance of considering scale, especially across large lakes that exhibit marked complexity and a variety of freshwater habitats.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.018
GPT teacher head0.222
Teacher spread0.204 · 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

Citations47
Published2014
Admission routes1
Has abstractyes

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