Characteristics of Buffalo Production and Research Systems in Southern Mexico
Bibliographic record
Abstract
Background: This research aimed to characterize the production units of water buffalo (Bubalus bubalis) and review the published scientific literature in southeastern Mexico. Methods: Between May and June 2020, a questionnaire was created in Google forms, distributed through social networks, and emailed to buffalo breeders. In addition, a review of different scientific databases on the experimental studies developed in Mexico on buffalo was performed. Results: Data was collected from 8,867 animals from 13 producers located in southeastern Mexico; dual-purpose (milk-meat) is the primary zootechnical purpose (69.24%), and the rest is meat production. The buffalo herd is mainly composed of females (72.09%). Females are used primarily to repopulate the herd and males for meat production. Mortality in adults remained between 2 to 5%. 30.76% of the producers produce milk (495 females) with 5.1 L/d on average. 100% of the producers stated that they transform the milk into dairy products, mainly cheeses and other products. In the case of meat production, 31.97% of the males are fattened based on pastures with a weight range between 400-600 kg at the age of 22 months (range 18-30 months). Between 2012-and 2021, 19 studies related mainly to herd health (63.15%) were registered. Conclusion: It is concluded that this Mexican species has great productive potential with different areas for improvement. Due to sanitary management and rusticity, mortality is low. It is necessary to develop other lines of research associated with the reproduction, production of milk/meat, health, quality of products, safety, and sustainability of buffalo activity in Mexico.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".