Growth performance, carcass characteristics, and meat quality in meat and dairy goat kids fed a concentrate-based diet or allotted to an intensive rotational grazing system
Bibliographic record
Abstract
Forty meat or dairy kids were blocked within breed according to body weight. Kids within each block were then randomly allotted to a concentrate-based diet or an intensive rotational grazing system. Kids fed the concentrate-based diet were offered hay ad libitum and fixed amounts of whole corn and soybean meal to meet the requirements for maintenance and daily gain. Grazing kids from each breed were stocked in groups and offered a new paddock every day. Dry matter intake was not different between breeds. Meat kids had a greater average daily gain than dairy kids, but feeding treatments did not affect the growth rate. Dairy kids had greater anterior cuts (neck and shoulder), whereas meat kids tended to have greater posterior cuts (loin and leg). Meat kids accumulated more fat when they were fed concentrate in comparison with pasture, whereas this variable tended to be less influenced by dietary treatments in dairy kids. Meat of pasture-fed kids had greater Warner–Bratzler shear force and glycolytic potential, and lower ultimate pH than meat of concentrate-fed kids. The n-6/n-3 fatty acid ratio of intramuscular fat was almost 4-fold greater in concentrate- than pasture-fed kids; this ratio was 1.4-fold greater in dairy than meat kids.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".