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Record W4382359607 · doi:10.1139/as-2022-0043

Morphology of Arctic cod (<i>Boreogadus saida</i>) assessed according to habitat preference and age in the Beaufort Sea

2023· article· en· W4382359607 on OpenAlexafffundvenue
Juliano Malizia, Marie Launay, Ingrid Marie Bruvold, María Quintela, Torild Johansen, James D. Reist, Andrew Majewski, Denis Roy

Bibliographic record

VenueArctic Science · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans CanadaMcGill University
FundersFonds de recherche du Québec – Nature et technologiesFisheries and Oceans CanadaUniversities Space Research AssociationNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsArcticHabitatMarine habitatsMarine ecosystemTrophic levelEcologyFisheryEcotypeBeaufort scaleEcosystemSea iceClimate changeGeographyBiologyOceanographyGeology

Abstract

fetched live from OpenAlex

The Arctic cod ( Boreogadus saida (Lepechin, 1774)) represents the most widespread and abundant fish in the Arctic and is a critical trophic link in its ecosystems. Like many species endemic to the region, it has lost essential habitat as the extent and thickness of sea ice have declined substantially in recent decades. Extreme warming induced by climate change continues to deteriorate polar marine environments. Thus, understanding how Arctic cod use and partition their habitat/environment is central to their conservation. We assessed Arctic cod functional morphology using traditional (including gill rakers) and geometric morphometrics and explored whether these differed among primarily depth-based habitats and age classes using multivariate techniques. While distinct ecotypes have been proposed, these were not detected in our analyses. Rather, results show similar patterns in external morphology of Arctic cod across habitats and age classes in the Beaufort Sea. However, analysis of gill rakers revealed concurrent habitat- and age-specific changes likely associated with dietary preferences. Findings indicate that although Arctic cod do not specialise in external morphological features in any habitat, important aspects of their internal feeding morphology shift as they grow, likely underpinning important distributional shifts and its critical role in transferring energy in Arctic marine ecosystems.

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)0.002
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 score0.018
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.048
GPT teacher head0.295
Teacher spread0.247 · 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

Citations2
Published2023
Admission routes3
Has abstractyes

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