The importance of dietary phosphorus and highly unsaturated fatty acids for sockeye (<i>Oncorhynchus nerka</i>) growth in Lake Washington a bioenergetics approach
Bibliographic record
Abstract
Juvenile sockeye salmon (Oncorhynchus nerka) in Lake Washington experience very high growth rates, but the mechanisms regulating their growth rates are poorly understood. The potential for food quality limitation of growth was tested using a coupled bioenergetics and mass balance model. Sockeye and zooplankton prey species were analyzed for their fatty acid composition. Ratios of phosphorus to carbon (P:C) for both sockeye and zooplankton were obtained from the literature. Based on sockeye stomach contents and zooplankton weights, diets of zooplankton biomass were calculated and monthly values of specific fatty acids and P:C ratios in the diet were derived. An increase in highly unsaturated fatty acids, especially in the liver, was observed with increased fork length up to smoltification size, with a subsequent decrease in smolts and kokanee. Measurements of docosahexaenoic (DHA) in daphnids were significantly lower than in cyclopoids. Model predictions suggest that sockeye are not limited by the availability of phosphorus or eicosapentaeinoic acid (EPA) in their diet but may experience limited growth because of DHA deficiencies. Thus, the ability and efficiency of sockeye at elongating 18:3 ω3, 18:4 ω3, and EPA to DHA may be of critical importance to lacustrine growth and production.
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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) | 0.000 | 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".