0116 Associations of hygiene and lying behavior with the risk of elevated somatic cell count and lameness
Bibliographic record
Abstract
The objective of this study was to identify how cow-level factors and housing management affect the risk of elevated SCC (eSCC) and lameness in lactating dairy cows. Cows from six commercial free-stall dairy herds in Ontario, Canada, were enrolled in a longitudinal study. Ten Holstein cows/herd were randomly selected based on days in milk (DIM; <120 d), absence of mastitis treatment in the last 3 mo, and somatic cell count (SCC < 100,000 cells/mL). Data on SCC were collected through DHI testing (∼5 wk intervals). The study began within 7 d after a DHI-milk test, continued until three tests were completed (∼105d), for a total of three observation periods/cow. Elevated SCC was used to indicate subclinical mastitis. An incident of eSCC was defined as a cow having a SCC > 200,000 cells/mL at the end of a period when SCC was <100,000 cells/mL at the beginning of that period. Lying behavior was recorded for 6 d after each milk sampling using data loggers. On d 1 of each recording period, a trained observer scored cows for lameness (5-point numerical rating scale, NRS ≥ 3 = lame). Hygiene scoring (four-point scale), also done by a trained observer, occurred on each visit. Cows were categorized as clean (1, 2) or dirty (3, 4). Stall cleanliness was assessed with a 1 m2 metal grid, containing 88 squares, centered between stall partitions of every 10th stall, and then counting the squares containing visible urine and/or fecal matter. Data were analyzed using multivariable logistic regression models. Cows averaged (mean ± SD) 627 ± 107.7min/d lying, 9 ± 2.8 lying bouts/d, and 72 ± 19.9 min/bout. Over the study period, 13 eSCC were detected, resulting in an incidence rate of 0.73 eSCC/cow-year at risk. The risk of experiencing an eSCC increased 1.4× (P < 0.01) with every 20,000 cells/mL SCC increment at the beginning of the study. Mean proportion of soiled squares/stall was 27%. Each SD (18.8%) increment in proportion of dirty squares/stall was associated with lameness (NRS ≥ 3; OR = 1.5; P = 0.05) and increased the odds of having a dirty udder (DU; OR = 2.4; P = 0.02). Each SD (108min/d) increment in lying time/d increased the risk of having dirty upper legs and flank (DULF; OR = 2.1; P < 0.01), and tended to increase the risk of having a DU (OR = 1.44; P < 0.08). For each 9.6% increase above mean (100%) cow/stall stocking density, the risk of having DULF increased by 1.7× (P = 0.03). These results indicate that lower stocking density and management practices that improved stall hygiene and should be encouraged to reduce the risk of poor hygiene and clinical lameness in dairy cows housed in free-stall barns.
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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 | 0.000 | 0.000 |
| 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) | 0.004 | 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".