Assessment of inter-regional dietary differences in anadromous Arctic char (<i>Salvelinus alpinus</i>) in Nunavik, Canada, and links with flesh quality indicators
Bibliographic record
Abstract
Arctic char ( Salvelinus alpinus) is a salmonid fish that is the second-most consumed country food species by Nunavimmiut. Its nutritional quality is determined by omega-3 fatty acids and carotenoid pigments. Those molecules cannot be synthetized by fish and must be acquired through diet. We sampled Arctic char in 10 rivers from the three marine coastal regions of Nunavik (Hudson Bay, Hudson Strait, and Ungava Bay), described diet (stable isotopes δ13C and δ15N) and flesh quality (fatty acids and carotenoids, measured by chromatography) and assessed associations between both diet and flesh quality (including also bio-impedance and colorimetry). Our results suggested inter-regional differences in the diet and nutritional quality of Arctic char in Nunavik, where δ13C values indicated that the diet of Arctic char in Hudson Bay was more pelagic, while in Ungava Bay it was more coastal. We also observed inter-regional differences in omega-3 fatty acids and astaxanthin, the pigment responsible for the redness of the flesh color, where concentrations were highest in Ungava Bay Arctic char. In all sampling locations, Arctic char were an exceptional source of omega-3 fatty acids and astaxanthin, confirming its importance as a high-quality wild food. Our models suggest that astaxanthin, canthaxanthin, and water content influence flesh redness. Our data highlight inter-regional differences that could be taken in consideration to better predict the impact of climate change on fish quality and, ultimately, on Inuit diet and health.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".