A dairy herd-level study of postpartum diseases and their association with reproductive performance and culling
Bibliographic record
Abstract
The objectives of this study were to quantify the herd-level prevalence of postpartum diseases in a large number of dairy farms, and to identify prevalence alarm levels of these diseases based on association with a low prevalence of success at first service, with a high prevalence of pregnancy loss following pregnancy diagnosis at first service, and with a high prevalence of postpartum culling. A total of 126 commercial dairy herds were enrolled in this cohort study, and the herd was the unit of interest. Twenty cows from every herd were enrolled during the study period (a total of 2,520 lactating cows in the study). Cows were diagnosed with hyperketonemia, retained placenta, displaced abomasum, purulent vaginal discharge, cytological endometritis, leukocyte esterase endometritis, and prolonged anovulation. The prevalence of each of these diseases was computed for every herd. The study outcomes were the prevalence of success at first service, the prevalence of pregnancy loss following pregnancy diagnosis at first service, and the prevalence of postpartum culling (≤60 d in milk). Descriptive statistics of disease and outcome prevalence were computed. Logistic regression models were used to identify prevalence alarm levels associated with poor outcome prevalence. Median herd prevalence for hyperketonemia, retained placenta, displaced abomasum, purulent vaginal discharge, cytological endometritis, leukocyte esterase endometritis, and prolonged anovulation were 18.8, 4.9, 4.0, 5.0, 29.4, 43.8, and 35.2%, respectively. Herds were defined as having low prevalence of success at first service if <40.0%, as having a high prevalence of pregnancy loss if ≥6.3%, and as having a high prevalence of postpartum culling if ≥13.3%. Risk factors for herds having a low prevalence of success at first service were ≥11.8% hyperketonemia, ≥5.0% purulent vaginal discharge, ≥18.8% cytological endometritis, ≥35.3% leukocyte esterase endometritis, ≥21.0% prolonged anovulation, and ≥4.0% of displaced abomasum. Risk factors for herds having a high prevalence of pregnancy loss were ≥5.0% purulent vaginal discharge and ≥4.9% retained placenta. Risk factors for herds having a high prevalence of postpartum culling were ≥23.1% hyperketonemia, ≥4.9% retained placenta, and ≥4.0% displaced abomasum. Overall, postpartum diseases were prevalent in these dairy herds and alarm levels were identified as risk factors for poor reproductive performance and increased culling.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".