Quarter-Level Milk Yield Recovery Following Clinical Mastitis: Associations with Milk Loss, Somatic Cell Count, Clinical Severity, and Pathogens
Bibliographic record
Abstract
Understanding milk yield recovery following clinical mastitis (CM) and its influencing factors is essential for controlling the effect of mastitis on milk yield. This study investigated the associations between quarter-level milk yield recovery and milk loss, somatic cell count (SCC), clinical severity, and causative pathogens. Recovery was measured as percentage recovery for inflamed and uninflamed quarters separately. We analyzed 117 CM cases, identifying 117 quarter-level milk yield perturbations (qMYPs) in inflamed quarters and 299 in uninflamed quarters. The recovery of qMYPs was compared across quickly, slowly, and non-recovered groups for inflamed and uninflamed quarters, based on the average and slope of percentage recovery over time, using the Mann–Whitney test. Correlation and regression analyses were conducted to assess associations with milk loss, SCC, clinical severity, and pathogens. Inflamed quarters showed similar recovery to uninflamed quarters in recovered groups but significantly worse recovery in the non-recovered group (p < 0.05). In inflamed quarters, greater milk loss, higher SCC, more severe clinical signs, and major pathogens were associated with worse recovery (correlation < 0). In uninflamed quarters, these factors were linked to worse early recovery (correlation < 0), whileled to improved recovery over time (correlation > 0). Additionally, short-term and long-term recovery were influenced differently in inflamed and uninflamed quarters. These findings improve understanding of CM recovery and may support selective treatment, reduce disease impact, and enhance animal welfare in dairy production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".