Optimizing Prepared Feed Ration for Gonad Production of the Green Sea Urchin <i>Strongylocentrotus droebachiensis</i>
Bibliographic record
Abstract
Abstract Adult green sea urchins Strongylocentrotus droebachiensis were fed three different quantities (0.25, 0.50, 1.00% body weight/d) of a prepared feed during a 12‐wk experiment to determine the effect of food ration on gonad quantity and quality. A diet of kelp, Laminaria longicruris and/or L. digitata, fed at satiation (3% body weight/d) and urchins taken from the wild at the beginning and end of the experiment served as controls. Urchins fed prepared feed or kelp increased their percent gonad yield significantly over the experimental period. Affer 12 wk, individuals fed the prepared diet at 0.50 or 1.00% body weighffd had significantly higher percent gonad yields (mean ± SEM: 23.5 ± 0.6% and 23.4 ± 0.7%, respectively) than urchins fed at 0.25% body weight/d (18.0 ± 1.0%) or control animals given kelp (18.3 ± 0.8%). There was no significant difference in gonad yield between the 0.50 and 1.00% feeding levels. All feeding treatments had significantly higher percent gonad yields than urchins sampled from the wild at the end of the experiment that had recently spawned (2.8 ± 0.5%). There was no significant difference in gonad taste among urchins fed the prepared diet at 0.25% body weight/d, those given kelp, or those collected from the wild at the end of the experiment (good to very good ratings), but all of these treatments had significantly better tasting gonads than urchins given the prepared feed at 0.50 or 1.00% body weight/d (satisfactory ratings). Gonad taste rating of urchins fed a prepared diet was dependent on ration with greater feed amounts leading to worse tasting gonads (linear regression: r2= 0.68, P < 0.01). Gonad color, texture, and firmness did not differ significantly among any of the feed ration treatments or kelp control. Results suggest that the best ration for prepared feed would be 0.50% body weightld since this would optimize gonad yield while minimizing feed costs. Further research on prepared feeds is required to optimize both gonad color and taste.
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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".