Animal Performance and Carcass Characteristics of Crossbred Bulls Finished in Different Production Systems in the Tropics
Bibliographic record
Abstract
Extensive beef systems in the tropics are the cheapest but require more land and longer rearing times with environmental impact. This study was carried out to evaluate three beef bull’s production systems in tropics: pasture-based system (PASTU), feedlot system immediately after weaning (FELOT) and a system with the combination of rearing in pasture and finishing in feedlot (PRIME) on animal performance and carcass characteristics of 30 bulls crossbred Angus x Nellore. The final weight, average daily gain and carcass weight (hot and cold) were higher (p < 0.050) for the FELOT system, intermediate for the PRIME system and lowest for the PASTU system. The carcass dressing (hot and cold), dripping losses, ratio (Longissimus dorsi) and degree of finishing were similar (p > 0.050). The carcass pH24h was higher for the PRIME system (p < 0.010). Subcutaneous fat thickness (mm) was lower for the PASTU system (p < 0.050). Marbling was better for the PRIME system. The tissular composition was similar among systems related to muscle percentage but PASTU showed the highest bone percentage (p < 0.050) and lowest of adipose (p < 0.050). PRIME enable cost-effective, fast beef production with less environmental impact.
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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".