167 Addition of garlic powder at low doses stimulated mineral consumption in feedlot cattle
Bibliographic record
Abstract
Abstract The trial evaluated whether the addition of garlic powder increased mineral intake and reduced fly abundance in feedlot cattle. Following a completely randomized design, one hundred and four (104) spring-born crossbred steers (BW 529 ± 8kg) were recruited for the feeding trial at Lakeland College, Vermilion Alberta, Canada. Each steer was assigned to one of four treatment groups (26 steers each) where each group received a commercial feedlot mineral mixed with garlic powder to give a final supplement mix that contained either 2.5% or 5% garlic powder or 0.3% garlic-oil-based premix or 0% garlic product (as control). The animals received a feedlot ration. The different treatment groups were kept within side-by-side pens, each equipped with water troughs and automatic feeding equipment to measure individual feed and mineral consumption. Feed and mineral supplements were provided ad libitum. Differences were observed for mineral intake (P = 0.003), ADG (P = 0.002) and feed conversion efficiency (P = 0.01). Compared to the control, mineral supplement consumption increased between 18 to 50% in groups that received garlic-infused supplements. Fly counts did not differ among the groups, in part, due to low overall fly abundance. While there were no differences (P = 0.21) in the length of time the steers spent consuming feed, differences existed for time spent consuming minerals (P = 0.002) and mineral bunk visits (P = 0.0003). There was no difference (P > 0.18) in DMI, final body weight or hot carcass weight among the different groups. The hematological and biochemical parameters were within normal ranges for healthy cattle, and there was no difference in carcass quality grades (P = 0.78). Even though the impact on fly-counts was inconclusive, the preliminary results show that including low-dose garlic powder could be a practical strategy of increasing mineral consumption without any associated negative health consequences.
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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) | 0.001 | 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) | 0.001 | 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".