The Fatty Acid Profile of Eulachon (Thaleichthys pacificus) Grease: An Invaluable Traditional Food of the Coastal First Nations of British Columbia
Bibliographic record
Abstract
A lesser-known and under-studied, but prized oil-rich fish species for coastal First Nations of British Columbia is the eulachon (Thaleichthys pacificus). Each family has individual techniques to ferment, cook, and strain this cultural keystone species to render the fat, often called "grease" (ṫli'na) which is of great cultural, nutritional, social, and economic value. In this study, the nutritional profiles of eulachon grease are explored by chemical analysis and traditional knowledge obtained through interviews with Knowledge Holders. Lipidomic techniques were applied using two different chemical analysis methods (i.e., gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry) to identify and quantify the individual fatty acid levels in seven eulachon grease samples collected in Alert Bay, BC, in July 2023. Fish oil supplement samples were bought from the Canadian market in January 2023 and analyzed for comparison. The results show that there are significant variations in the lipid profiles of the eulachon grease samples regardless of preparation techniques (i.e., length of eulachon fermentation, cooking, etc.). Eulachon grease samples contain unique saturated, polyunsaturated, and monounsaturated fatty acids that are beneficial to health (i.e., promote cardiovascular health, reduce the risk of cardiovascular diseases, and provide anti-inflammatory, immunoregulatory, and neuroprotective effects). In comparison, fish oil supplements from the Canadian market were found to have relatively high levels of saturated fatty acids. Traditional Knowledge also supports the many benefits of eulachon grease. Eulachon grease fills a critical niche in the diet, health, and well-being of BC coastal First Nations People.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".