Behaviour and Welfare of Dairy Buffaloes: Pasture or Confinement?
Bibliographic record
Abstract
This review seeks to integrate recent scientific findings on the behaviour of buffalo cows in different production systems. These issues are discussed in relation to the level of welfare that buffalo cows experience under different production systems. In extensive conditions, the level of welfare is high because the animals are free to express natural behaviours related to feeding (grazing, ruminating) and rest. In contrast, intensified livestock-raising methods and techniques (machine-milking, artificial breeding etc.), first developed for dairy cattle are increasingly being used with water buffaloes in order to increase milk production. Greater knowledge of the biology of dairy buffaloes in aspects linked to physiology, behaviour, and health, together with needed adjustments to their production systems, will indicate options for improving the levels of comfort and welfare of these animals and contribute to increasing the efficiency of this type of dairy production. It is necessary to appreciate the importance of welfare within the entire chain of animal production since each of the scientific aspects considered in this manuscript reflects that animal welfare is not an absolute term, but multidisciplinary, with direct consequences on productivity. The welfare of animals in the production systems must be considered with the aim of ensuring an adequate nutritional, clinical, sanitary and behavioural status of the animals. When these aspects are achieved, production can be maximized and, for this reason, it is essential to maintain a balance between welfare and productivity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".