Growth and fur characteristics of blue foxes (<i>Alopex lagopus</i>) fed diets with different protein levels and with or without DL-methionine supplementation in the growing-furring period
Bibliographic record
Abstract
A production trial was carried out on 125 growing-furring blue foxes (Alopex lagopus) to study the effects of low-protein diets, with or without DL-methionine supplementation, on growth performance and fur characteristics. The treatment codes were P30, P22.5, P22.5M, P15, and P15M. The protein contents [g kg -1 DM (dry matter)] of the diets were 300, 243, 243, 174, and 177, respectively. DL-methionine was added to P22.5M and P15M to yield a total dietary content of methionine (M) corresponding to that in P30. From August to mid-September, the weight gain of the blue foxes receiving the diet with the lowest protein level and the lowest methionine content (P15) was significantly lower than that of the blue foxes in treatments P22.5 and P30. In contrast, growth of the blue foxes in P15M did not differ from that of the blue foxes in P22.5 or P22.5M. From mid-September to pelting, weight gain did not differ significantly among treatments. Guard hair quality was significantly impaired in the low-protein diets without methionine supplementation, but not in those diets supplemented with methionine. Methionine appeared to be the first limiting amino acid for winter fur development. Addition of DL-methionine and use of low-protein diets for blue foxes would be beneficial in terms of reduced feed expenses and lower nitrogen emissions to the environment. Key words: DL-methionine, protein, amino acids, growth, fur skin quality, blue fox (Alopex lagopus)
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".