Effects of feeding blend-pelleted co-products on nutrient intake, digestibility, and production performance of high producing dairy cows
Bibliographic record
Abstract
The objectives of this study were to examine the effects of feeding newly developed blend-pelleted carinata meal (BPPCR) and blend-pelleted canola meal (BPPCN) on nutrient intake, digestibility, and production performance of high producing dairy cows. In this study, nine mid-lactating Holstein cows (body weight, 679 ± 124 kg; days in milk, 96 ± 22) were used in a triplicated 3 × 3 Latin square study. Within each square, each cow was randomly assigned to one of three treatments: control (typical barley-based diet in Western Canada), BPPCR (soybean and canola meal in the control diet replaced by BPPCR), and BPPCN (soybean and canola meal in the control diet replaced by BPPCN). Each period lasted for 21 d, with the first 14 d as an adaptation period. The total collection of feces and urine were conducted on six cows from two Latin squares. The results showed that there were no treatment effects on milk yield, milk composition, and nutrient intake and digestibility (P > 0.10). The nitrogen balance among the three treatment groups was not different either. In conclusion, replacing soybean meal and canola meal with blend-pelleted co-products did not affect the nutrient intake, digestibility, and production performance in high producing dairy cows.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".