Carcass cut-out value and eating quality of longissimus muscle from serially harvested savannah-raised Brahman-influenced cattle and water buffaloes in Venezuela
Bibliographic record
Abstract
Males (n = 132) of riverine water buffalo (Buffalo) and Brahman-influenced cattle (Brahman) were reared alike and serially harvested at four different ages (7, 17, 19 and 24 months) to compare cutting yield (%), eating quality and consumer acceptability of cube-roll steaks at 19 and 24 months of age (MOA), and to examine post-weaning castration effects. Brahman bulls outperformed Brahman steers and Buffalo male classes in the proportion of chuck-roll, medium-value and total valuable cuts (P < 0.05). At all harvest ages, Buffalo carcasses yielded higher (P < 0.05) percentages of trimmed fat, which resulted in a sustained decline of the proportion of total lean, edible cuts. Buffalo meat had a lower shear-force value and a higher proportion of tender steaks than did Brahman at 7 and 24 MOA (P < 0.05). Whereas trained panellists detected differences in sensorial attributes only at 7 months [when Buffalo steaks were rated as more tender and flavourful (P < 0.05) than Brahman steaks], consumer acceptability ratings for Buffalo meat trended to be higher when harvested at 19 and 24 MOA (P < 0.1). The increasing proportion of boneless lean cuts with age gives Brahman a clear, commercial advantage over Buffalo; however, Buffalo produces meat as juicy and flavourful as that of Brahman and exhibits superior eating quality if harvested at 7 or 24 MOA.
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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 | 0.000 |
| 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".