Morphology of Arctic cod (Boreogadus saida) assessed according to habitat preference and age in the Beaufort Sea
Bibliographic record
Abstract
Arctic cod (Boreogadus saida) 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 uses and partitions its habitat/environment is central to its conservation. We assessed Arctic cod functional morphology using traditional (including gill rakers) and geometric morphometrics and explored whether these differed among 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 the 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 does not specialise in external morphological features in any habitat, important aspects of its internal feeding morphology shift as it grows, likely underpinning important distributional changes and the species' critical role in transferring energy in Arctic marine ecosystems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".