Preliminary Results of an Observational Study describing the Relationship between Milk Urea Nitrogen and Pasture Management in Prince Edward Island Dairy Herds
Bibliographic record
Abstract
The initial phase of a long term milk urea nitrogen (MUN) project consisted of a six month (May - Oct 99) observational study 75 dairy herds in Prince Edward Island, a temperate-climate, maritime province on the east coast of Canada. Several studies have shown that MUN levels increase when cows are put on pasture (1, 2, 5 ). Ubertalle (4) found that MUN levels were related to grass quality and composition. Lean (5) reported that as pasture develops, the energy content and protein percentage of the dry matter (DM) decreases. Intensive pasture management reduces back grazing and promotes pasture regrowth (5), allowing the energy content and protein percentage of the dry matter (DM) to persist longerthan with low-intensity pasture management. This study describes the relationship between pasture management, precipitation, and observed MUN levels in dairy herds.
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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 | 0.000 | 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".