Investigations of Milk Quality from Teats with Milk Flow Disorders
Bibliographic record
Abstract
The objective of this study was to investigate the quality of milk from teats with milk flow disorders. Somatic cell count, pathogens, and signs of mastitis (>100,000 cells/ml and pathogens detected) were determined in the milk from all teats of the udder before treatment of the affected teat, as well as 1 and 6 mo later. Teats with milk flow disorders were compared to all of the other teats from the same udder. Before treatment, the SCC from affected teats was 4.3 million higher, the odds of detecting pathogens 6 times higher, and the odds of mastitis 11 times higher than in control teats (when adjusted for other significant explanatory variables). SCC and the risk of mastitis decreased after surgical treatment of the affected teats, whereas the chance of detecting pathogens was not affected. Six months after treatment, the SCC was 1.3 million higher, and the odds of mastitis 6.5 times higher than in control teats. Throughout the study period neither SCC, the odds of detecting pathogens, nor mastitis changed significantly in control teats. It may be concluded from this study that milk quality from teats with milk flow disorders is decreased before treatment and does not reach the milk quality from unaffected teats within 6 mo after treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".