Effects of dietary total non-structural carbohydrates and folic acid and vitamin B<sub>12</sub> supplement on growth and meat quality of yearling steers in a forage-based beef production system
Bibliographic record
Abstract
Mercier, J., Cinq-Mars, D., Berthiaume, R., Faucitano, L. and Girard, C. L. 2015. Effects of dietary total non-structural carbohydrates and folic acid and vitamin B12 supplement on growth and meat quality of yearling steers in a forage-based beef production system. Can. J. Anim. Sci. 95: 281–291. Thirty-two spring calving cows [760±91 kg body weight (BW)] and calves (44±4.5 kg BW) were assigned to eight blocks of four cows and their calves each according to parity and calving date. Within each block, two cows were fed a low total non-structural carbohydrate (TNC) diet, while the two others were fed a high TNC diet. Within each diet, cows were administered either no vitamins or weekly intramuscular injections of 160 mg of folic acid plus 10 mg of vitamin B12. Calves were slaughtered at 305±9 d. Neither TNC concentration nor vitamin supplementation affected (P>0.10) milk yield but the vitamin supplementation increased (P=0.002) milk concentrations of vitamin B12. There was no treatment effect on calf performance, or carcass and meat characteristics (P>0.10) except for collagen concentrations and shear force measurements in the longissimus lumborum muscle, which had a tendency to be decreased (P≤0.06) by the vitamin supplement. In the present study, differences in forage TNC concentrations did not influence cow and calf performance. Moreover, folic acid and vitamin B12 supplements were shown to have little impact in this study on growth of beef cattle.
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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) | 0.000 | 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 | 0.001 |
| 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".