Omega-3 Fatty Acids in Fish from the Laurentian Great Lakes Tribal Fisheries
Bibliographic record
Abstract
Dietary fish must be assessed for benefits and risks to formulate risk management strategies. This article demonstrates that Laurentian Great Lakes (GL) freshwater species are good sources of omega-3 fatty acids using new data from a small sample (n = 7) of Lake Superior siscowet lake trout (Salvelinus namaycush siscowet) and five other GL fish species’ data. For Lake Superior (LS) siscowets, the saturates, mono-unsaturates, and poly-unsaturates composed 20.1, 40.7, and 39.1% of total lipid weight, respectively. Omega-3 poly-unsaturates (PUFAs) in these fish were more than twice the omega-6 (omega 3/6 ratio = 2.4). The LS lake trout data were combined with earlier LS data collected during the 1980s for eight other species and from five species of Lake Erie fish. All the GL freshwater species were compared with seven other published marine and freshwater fish studies from other global regions. PUFAs were compared based on latitude and marine versus freshwater origin. Differences between marine and freshwater species in omega-3 fatty acid were less at higher latitudes. GL freshwater fish species can be a good source of beneficial fats like marine fish and must be accounted in effective risk communications involving persistent bioaccumulative toxicants in dietary fish.
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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".