Nutritional, managerial, physiological, and environmental factors affecting milk urea nitrogen in Quebec Holstein cows : a field trial
Bibliographic record
Abstract
This trial was carried out in order to elucidate factors affecting milk urea nitrogen (MUN). Twenty-five herds were selected for MUN testing. Three sampling periods were chosen. The first occurred during the months of March and April, the second during July and August, and the third during November and December 1997. A total of 2,686 samples were collected and analyzed. Two different methods were employed for MUN analysis and were referred to as the Macdonald Campus method (MUN-MAC) and the Programme d'Analyse des Troupeaux Laitiers du Quebec method (MUN-P.A.T.L.Q.). The MUN-MAC consists of an enzymatic method while the P.A.T.L.Q. method is an infra-red method. Prior to initiation of the trial, the MUN-MAC method was validated and found suitable for use in this experiment. The results demonstrated that the factors which significantly contributed to the models were the ration's net energy of lactation, season, region, somatic cell count, total dry matter, neutral detergent fiber, non-structural carbohydrates, total fat, crude protein, protein to energy ratio, starch to protein ratio, parity and days in milk. (Abstract shortened by UMI.)
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".