Assessing the link between ontogenetic shifts in gill raker and diet composition of Arctic cod Boreogadus saida in the Canadian Beaufort Sea-Amundsen Gulf
Bibliographic record
Abstract
Arctic cod Boreogadus saida represents the most widespread and abundant fish in the Arctic Ocean and is a key trophic link in Arctic marine ecosystems. As the Arctic undergoes further rapid warming, understanding the ecological dynamics of this species is critical for developing effective Arctic marine conservation efforts. In this study, we assessed the relationship between ontogenetic shifts in gill raker density and diet composition of Arctic cod in the Canadian Beaufort Sea-Amundsen Gulf, using diet analyses and dietary tracers. Our results support the hypothesis that ontogenetic changes in gill raker density are associated with age-specific dietary shifts, leading to changes in the species’ habitat preferences, from surface to deeper waters in the Canadian Beaufort Sea-Amundsen Gulf. As Arctic cod mature, their gill raker density decreases, making them less efficient at foraging on small prey found near the surface. Older fish, with sparser gill rakers, likely relocate to deeper areas to forage on larger prey, as reflected in their diet item sizes, proportions, and dietary tracers. These insights improve our understanding of how gill raker density, along with factors such as predation and thermoregulation, likely drive diet and habitat shifts in Arctic cod, contributing to our knowledge of their ecological role in Arctic marine systems.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".