Evaluation of the use of commercial-type and synthetic diets to test a nucleotide-rich yeast-derived product as a growth promotor for first feeding rainbow trout fry raised at 10 or 16 °C
Bibliographic record
Abstract
A nucleotide-rich yeast-derived product (Maxi-Gen™; CBS Bio Platforms, Inc., Calgary AB, Canada), was fed to rainbow trout fry housed at 10 or 16 °C to determine its effect on weight gain and feed intake. Rainbow trout fry housed in 40 16 L tanks (25 fish/tank) were fed commercial-type or synthetic diets with or without the nucleotide-rich yeast product added (0% or 0.5% inclusion) until they reached 60 days of age (5 tanks/4 diets/2 temperatures). Fish housed at 16 °C consumed significantly more feed and gained significantly more weight than fish housed at 10 °C. Trout fed the commercial-type diet gained significantly more weight than those fed the synthetic diet without the nucleotide-rich yeast product added. There was no significant difference in weight gain or feed intake among fish fed either commercial-type diet and the fish fed the synthetic diets with the nucleotide-rich yeast product added, although fish fed the commercial-type diets had significantly better feed conversion efficiencies than those fed the synthetic diets. The nucleotide-rich yeast product could be used in low fish meal, low fish oil first feeding diets, as the aquaculture industry decreases fish meal and oil use in aquafeeds in response to their increasing cost and decreasing availability.
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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) | 0.001 | 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 | 0.001 |
| 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".