Measuring individual free-choice protein supplement consumption by wintering beef cattle
Bibliographic record
Abstract
Free-choice supplements provide protein, trace minerals, vitamins, salt and chemotherapeutic agents to cattle. For optimal benefit, a supplement should be consumed on a regular basis and at levels that do not vary significantly on a day-to-day basis. Many factors affect variability in supplement intake such as palatability of the supplement, competition between animals and the ease with which the supplement may be consumed. The aim of this study was to evaluate the differences between a solid molasses-block supplement and a liquid-molasses supplement with respect to intake and the associated behaviors (attendance, duration, and intake rate). Using a cross-over design, 34 pregnant cows weighing 720 ± 11kg were randomly allocated to two separate groups (n = 17 for each group) and evaluated for two 3-wk periods (24 February to 16 March 1999 and 25 March to 14 April 1999), using both forms of the supplement. The individual intake was recorded by way of an electronic feeding system, which made use of an electromagnetic field around the feeder in conjunction with electronic identification (EID) tags, which registered each animal’s unique eight-digit number. Cows fed the liquid supplement visited the feeder more often (P < 0.05) when compared to those fed the block supplement. The mean dry matter intake did not differ between the supplements (349 g head-1 for the block and 330 g head-1 for the liquid), but there were significantly larger deviations in intake for the block supplement than the liquid (P < 0.05) indicating more uniformity in daily intake with the liquid supplement. In almost all cases the liquid supplement was consumed at a faster rate (P < 0.05) and significantly less time (P < 0.05) was spent at the feeder. Free-choice administration of additives in liquid supplements, as compared to blocks, may result in a more frequent and less variable intake. Key words: Protein, intake, supplement, cattle, behavior
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".