Tropical Beef: Is There an Axiomatic Basis to Define the Concept?
Bibliographic record
Abstract
Cattle production in tropical regions has been estimated to account for just over half of cattle worldwide, yet it has not been demonstrated that sufficient similarities in the cattle exist to describe tropical cattle and, even less so, to characterize the meat from these animals. The aim of this review is to investigate the quality and nutrient composition of meat from cattle raised in the Tropics to determine if there is an axiomatic basis that would allow the definition of a concept of “tropical beef”. Tropical beef is the meat obtained from cattle raised in tropical environments, the population of which remains largely uncharacterized. Production systems in the Tropics are highly diverse but converge on the use of indigenous and Bos indicus breeds or Bos indicus-influenced crossbreeds under pasture feeding regimes. While some systems allow cattle to be slaughtered at ≤2 years of age, most often animals are ≥3 years. These production systems generally produce lean, low-yielding carcasses and tough (>46 N), lean (≤3.6% intramuscular fat) meat with a macronutrient composition otherwise similar to beef from animals raised elsewhere (72–74% moisture and 20–24% protein). Fatty acid profiles depend on the breed and production systems, while mineral content is influenced by the environment. Although lean and tough, tropical beef is highly acceptable to the consumers it serves, is culturally and traditionally relevant and, in many countries, contributes to food security. Consolidating the findings from animal and meat science studies in the Tropics has allowed the demonstration of an axiomatic basis defining “tropical beef” as a concept.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.012 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".