Fatty acid isotopic composition in Atlantic pollock is not influenced by environmentally relevant dietary fat concentrations
Bibliographic record
Abstract
Abstract The application of fatty acid (FA) isotopic analysis has great potential in elucidating food web structure, but it has not experienced the same wide-spread use as amino acid isotopic analyses. The failure to adopt FA isotopic methods is almost certainly linked to a lack of reliable information on trophic fractionation of FA, particularly in higher predators. In this work, we attempt to address this shortfall, through comparison of FA δ 13 C values in captive Atlantic pollock ( Pollachius virens ) liver and their known diets. Since catabolism is likely the main cause of fractionation and it may vary with dietary fat content, we investigated the impact of dietary fat concentration on isotopic discrimination in FA. We fed Atlantic pollock three formulated diets with similar FA isotopic compositions but different fat concentrations (5–9% of diet), representative of the range found in natural prey, for 20 weeks. At the conclusion of the study, δ 13 C values of liver FA were very similar to the FA within the corresponding diets, with most discrimination factors < 1. For all FA except 22:6n-3, dietary fat had no effect on discrimination factors. Only for 22:6n-3 did fish fed the highest fat diet have lower δ 13 C values than the diet consumed. Thus, these FA-specific discrimination factors can be applied to evaluate diets in marine fish consuming natural diets and will serve as additional and valuable biomarkers in fish feeding ecology.
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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 | 0.000 |
| 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".