Ecoregion and farm size differences in dairy feed and manure nitrogen management: A survey
Bibliographic record
Abstract
Sheppard, S. C., Bittman, S., Swift, M. L., Beaulieu, M. and Sheppard, M. I. 2011. Ecoregion and farm size differences in dairy feed and manure nitrogen management: A survey. Can. J. Anim. Sci. 91: 459–473. This paper describes the activity of dairy farmers in Canada in 2005 related to the use of nitrogen (N) and especially practices that led to loss of ammonia (NH3). The data were obtained from a large-scale, statistically structured survey conducted across Canada. The survey sampling was stratified into 10 Ecoregions and across farm size. Numbers of lactating cows per farm were nearly twofold more in the west than the east. In western Canada less than 31% of barns were “tie-stall” type whereas 80% were tie-stall in the St. Lawrence Lowlands. The numbers of hours lactating cows spent in barns, standing yards, exercise fields and pasture varied with Ecoregion and farm size, important data in relation to NH3 emissions. Pasturing was more common in the east than west. Matching feed crude protein concentrations to physiological needs seems a potential best management practice, and smaller farms with tie-stalls seemed more prone to adjusting feed to individual cows compared with large farms with loose housing. Manure handling was divided, with slurry prominent especially in the west. Manure spreading practices also varied by Ecoregion. Overall, it is clear that national averages do not well represent dairy farm management: Ecoregion and farm size differences are significant.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".