Assessment of tail-end dehulled canola meal for use in broiler diets
Bibliographic record
Abstract
The value of tail-end partially dehulled canola meal (DCM) was assessed in comparison to the conventional canola meal (CCM) from which it was derived using broiler chickens. CCM obtained from five crushing plants underwent the partial-dehulling. Nutrient retention was determined using 33-d-old broiler chickens and a 21 -d growth study was also conducted. DCMs contained a higher concentration of crude protein and amino acids and the utilization of energy and amino acids was improved. Energy utilization was also affected by crushing plant and there was an interaction between plant and meal type, suggesting that the dehulling was not uniform for meals obtained from the five plants. The DCM had higher digestibilities than the CCM (for 10 amino acids), but there were also plant effects for 7 amino acids. In the second experiment, feed intake, weight gain and mortality levels were not affected by tail end dehulling, but feed efficiency was. The similarity in chick performance and health between the chicks fed DCM and CCM indicates that there was no apparent concentration of anti-nutritional factors. In conclusion, although variability between crushing plants is a concern, tail-end dehulling has potential to increase the quality and marketability of canola meal for poultry diets. Key words: Dehulled canola meal, broiler chickens, metabolizable energy, amino acids, digestibility, growth
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".