Investigations on Milk Flow and Milk Yield from Teats with Milk Flow Disorders
Bibliographic record
Abstract
The objective of this study was to investigate peak milk flow, average milk flow, and milk yield in teats with milk flow disorders. A total of 100 hard milking teats were studied in 97 cows. Teats with milk flow disorders were examined endoscopically. Quarter milk flow and quarter milk yield were examined with four Lactocorders attached to a quarter milking machine. Peak milk flow, average milk flow, and milk yield were measured in 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 other teats of the same udder. Before treatment, peak milk flow from affected teats was 20%, average milk flow 14%, and milk yield 53% of the control teats, adjusted for other significant explanatory variables. Milk flow and milk yield increased after surgical treatment of the affected teats. Six months after treatment peak milk flow was 79%, average milk flow 76%, milk yield was 71% compared with control teats. We conclude from these findings that teat endoscopy and measuring quarter milk flow and milk yield with Lactocorders are useful tools for examining teats with milk flow disorders.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".