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Record W7028473130

Evidence for Three Morphs of Arctic Char (Salvelinus alpinus) Present in the Marine Environment Off the Coast of Ulukhaktok, Northwest Territories, Canada

2024· article· en· W7028473130 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2024
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsnot available
Fundersnot available
KeywordsArctic charArcticFish migrationPopulationMarine debrisMarine habitatsSubsistence agricultureLocal adaptationHabitatMarine conservationPlastic pollution
DOInot available

Abstract

fetched live from OpenAlex

Alternative resource use and responses to environmental conditions can lead to phenotypic diversity and distinct morphotypes within many anadromous salmonids, including arctic char. Arctic char is a culturally and economically important subsistence resource in the Inuvialuit Settlement Region (ISR).The current study examined char’s morphological plasticity during their summer marine migration where local harvesters have noticed a decrease in small sized individuals, but where limited knowledge exists on char morphology and population mixing in the area. Morphometric analysis was conducted using digital photographs taken of live arctic char collected during marine migration-residency along the Ulukhaktok coast. Twenty-three landmarks were placed on digital images of 103 fish and used to investigate the presence of different morphotypes, followed by PCA and K-means analyses. The results categorized fish into three clusters based on distinctions in head and body shape; slender body and slim head (n=31), small and short head with a small mouth (n=46), elongated head shape with large mouth (n=26). These three morphs likely represent adaptation to specific feeding—movement behaviours, correlated with unique origin lakes. This study represents the first to identify arctic char morphs in the marine environment and identifies overlap in their habitat use during the marine phase with implications for differential resource extraction. The derived information can inform fisheries management in the ISR and Ulukhaktok on likelihood of overfishing specific phenotypes that could potentially reduce stock diversity, ensuring long term sustainability of the fishery.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.537
Threshold uncertainty score0.921

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.248
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractyes

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