Cut and carry vs. grazing of cultivated pastures in small-scale dairy systems in the central highlands of Mexico
Bibliographic record
Abstract
Small-scale dairy systems are an option to alleviate poverty and contribute up to 37% of milk production in Mexico; however high costs affect their economic sustainability. Since grazing may reduce feeding costs, a participatory on farm experiment was undertaken to compare animal performance and feeding costs of the traditional cut-and-carry strategy or grazing cultivated pastures, during the dry season in the highlands of Mexico. Pastures of perennial and annual ryegrasses with white clover were utilised, complemented with maize silage and commercial concentrate. Five dairy cows were assigned to each strategy. The experiment ran for 12 weeks, recording weekly milk yields and fat and milk protein content; live-weight and body condition score every 14 days. Analysis was as a split-plot design. The adjusted (covariance) mean milk yield was 18.78 kg/cow/day with no significant differences (P>0.05) between treatments, and no significant differences for live-weight or body condition score. There were no significant differences for milk fat (P>0.05), but there were for protein in milk (P
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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 | 0.001 | 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".