Teat Anatomy and its Relationship with Quarter and Udder Milk Flow Characteristics in Dairy Cows
Bibliographic record
Abstract
Anatomical and functional characteristics of the teat are supposed to have considerable influence on milk flow performance. In the present study, various teat and milking characteristics in 148 quarters of 38 cows were analyzed via 3 different approaches. Teat canal length, teat wall thickness, and teat diameter were measured by ultrasound. In addition, the vacuum needed to open the teat canal (VO) was determined and milk flow profiles were measured in each quarter separately. Rear teats were shorter and thicker than front teats, whereas teat canal length and teat wall thickness did not differ according to quarter position. Milk yield and peak flow rate (PFR) were higher in rear than in front quarters. Teat canal length and VO were negatively correlated with PFR and average flow rate (AFR) but no correlations were observed between milkability traits and externally measurable teat characteristics like teat length or teat diameter. Individual milkability at an udder level is a complex characteristic that is determined by the milkability at a quarter level and the distribution of quarter milk yields. The anatomical and functional characteristics of single teats can partly explain the milk flow characteristics of individual quarters.
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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 | 0.000 |
| 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) | 0.000 | 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".