Effects of Varying Dietary Docosahexaenoic, Eicosapentaenoic, Linoleic, and α-Linolenic Acid Levels on Fatty Acid Composition of Phospholipids and Neutral Lipids in the Liver of Atlantic Salmon, <i>Salmo salar</i>
Bibliographic record
Abstract
Fish oil, the most abundant natural source of docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), is a limited resource; however, terrestrial oils are used as an alternative in fish nutrition. The liver of Atlantic salmon is able to synthesize these two long-chain n-3 polyunsaturated fatty acids (n-3LC-PUFAs) from α-linolenic acid (ALA), but the dietary levels of EPA + DHA and the ratios of linoleic acid (LNA) to ALA may affect its abilities. Feeding Atlantic salmon four experimental diets containing EPA + DHA at 0.3 and 1.0% of dietary levels accompanied with high and low LNA/ALA ratios showed that low LNA/ALA ratios increased the proportions of EPA + DHA in phospholipids (PLs) and neutral lipids (NLs). The pattern of PL-to-NL ratios of n-3 LC-PUFA proportions matched the saw tooth pattern of LNA/ALA ratios in diets. Overall, when fish oil is removed from salmon diets, the dietary LNA/ALA ratio must be reduced to stimulate biosynthesis of n-3 LC-PUFAs in the liver.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".