Effects of nutrition on larval growth and survival in bivalves
Bibliographic record
Abstract
Abstract This review examines the nutritional factors that influence the growth and survival of larval bivalves. Factors considered include feed form (live phytoplankton, preserved phytoplankton and artificial feeds) and feed biochemical composition (protein, lipid, carbohydrate and essential fatty acids). These factors, as they relate to larval production, are discussed in terms of growth and survival rates. To facilitate comparisons among larval studies, growth rates and feeding rates are standardized to common units. In addition, the standardized results for larvae of the Pacific oyster ( Crassostrea gigas Thunberg) are analysed using linear regression techniques to determine the strength of the correlations between daily doses of biochemical feed components and daily growth rates. Piecewise linear spline modelling is used to determine maximum effective dose response, the point where feeding additional biochemical components to the larvae yields no significant improvements in growth. Derived from these analyses are suggested daily rations of lipid, protein, carbohydrate, eicosapentanoic acid, docosahexanoic acid and energy for larvae of C. gigas .
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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".