Meat Quality of Dairy Steers Fed Mesquite Pod Meal in Semi-Arid
Bibliographic record
Abstract
The exploitation of dairy steers for meat production is an alternative to improve production rates, but feed alternatives to cereal grains like corn used in animal feed should be researched. In this study, we aimed to evaluate performance, carcass characteristics, and meat quality of dairy steers consuming different levels (0, 250, 500, 750, and 1000 g/kg, dry matter basis) of mesquite pod meal replacing corn. Twenty-five intact Holstein-Zebu dairy steers at approximately 18 months of age and with an initial body weight of 219±22 kg were used. A completely randomized design with five treatments (replacement levels) and five replications (animals) was adopted, and data were analyzed using PROC GLM for analysis of variance and PROC REG for regression analysis. There was no significant influence of the levels of replacement of corn by the mesquite pod meal as regards dry matter intake, final body weight, weight gain, carcass weight, or carcass yield (P > 0.05). The meat quality of the cattle was not significantly affected by the different levels of replacement (P > 0.05). Mesquite pod meal can fully replace corn in diets for dairy steers.
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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 | 0.000 |
| 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".