Effect of dietary bacterial protein or L-tryptophan supplementation on welfare and growth performance in silver fox
Bibliographic record
Abstract
The suitability of bacterial protein meal as a feed ingredient in silver fox diets was examined in an experiment comprising 72 juvenile silver foxes. Bacterial protein meal has a high content of tryptophan, which is the precursor for the neurotransmitter serotonin. The biological hypothesis on which this study was premised was that increased brain serotonin production reduces the fear response, which may lead to better welfare and performance through lower energy expenditure related to fear-induced defensive responses. The effect of substituting 15% fish meal with bacterial protein meal was measured by two behavioural tests, growth performance and fur quality, by comparison with a control diet and a diet supplemented with a high level of synthetic tryptophan. The welfare of the foxes fed the diet supplemented with synthetic tryptophan was considered to be improved, as they used shorter time to approach feed in the presence of a person; thus displayed less fear, than the other two groups after treatment. Weight gain of the foxes during 55 d did not differ among diets, and feed consumption was similar. Live grading of the foxes showed that the dietary treatments did not affect fur quality (P > 0.05). It is concluded that 15% bacterial protein meal can replace fish meal in dry silver fox diets and that a large supplement of tryptophan reduces fear of silver foxes kept in cages. Key words: Bacterial protein meal, tryptophan, serotonin, silver fox, welfare, performance
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".