Factors influencing the growth and survival of larval and juvenile echinoids
Bibliographic record
Abstract
Abstract Many factors can influence the growth and survival of larval and juvenile echinoids (e.g. diet type, food ration, stocking density, temperature, salinity, dissolved oxygen, water chemistry and settlement cues), but most of these factors have not been studied in detail with regard to most species targeted for commercial aquaculture production. This review summarizes the state of knowledge on factors influencing the growth and survival of larval and juvenile echinoids. Sea‐urchin larvae are typically reared with either Dunaliella tertiolecta Butcher or Chaetoceros spp. The optimum food ration is in the range of 3000–9000 cells mL−1 and 20 000–60 000 cells mL−1 for D. tertiolecta and Chaetoceros spp., respectively, the concentration depending on larval stage and stocking density. Larvae have been successfully cultured at densities of 0.25–5.00 individuals mL−1, but the optimum level appears to be 1–2 individuals mL−1. A variety of benthic diatom species, particularly Navicula spp., can serve as the initial food source for young juveniles. Older juveniles may be fed with various species of foliose macroalgae and/or prepared diets. Most research on larval and juvenile echinoids has been done using ambient salinity and temperature, but some work has shown the importance of temperature on growth rate.
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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".