Interaction of Somatic Cell Count and Quarter Milk Flow Patterns
Bibliographic record
Abstract
Milk flow parameters at udder and quarter levels were studied in relation to somatic cell count (SCC) and other risk factors for mastitis (bimodality, duration of decline, and duration of overmilking phase). Thirty-eight Holstein cows in their first to sixth lactations were investigated during 10 mo of lactation. Monthly milk samples were collected for SCC during morning milking. Quarter and udder milk flows were recorded daily. A cow was included if one quarter was found to have an SCC higher than 200 x 10(3) cells/mL. A total of 3,262 quarter milk flow curves and 804 udder milk flow curves from 22 cows (6 primiparous and 16 multiparous) were selected and evaluated. Selected data for milk flow profiles in relation to SCC represented 5 consecutive morning milkings around the time of milk sampling (sampling on d 3). A total of 661 milk samples were analyzed. At both the udder and quarter levels milk yield was reduced in groups with increased SCC. Quarters with high SCC (> 500 x 10(3) cells/mL) had lower peak flow rate and longer overmilking phases compared with quarters with low SCC (< 200 x 10(3) cells/mL). There was a tendency for a longer duration of the decline phase in quarters with high SCC but no effect was observed at the udder level. There were longer declines in bimodal milk flows at the quarter, but not at the udder, level. Also, quarters with bimodality had longer overmilking phases. The duration of the decline phases at the quarter level influenced all measured parameters except the duration of the increase phase. The quarters with a longer duration of the decline phase (> or = 80 s) had greater SCC and peak flow rate but had lower milk yield compared with quarters with a shorter duration of the decline phase (< 27 s). Duration of the overmilking phase influenced all measured parameters except SCC. We conclude that for good udder health, the duration of the decline phase at the quarter level should be considered for milking parameters and udder preparation before milking.
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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 | 0.001 | 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".