Definition and Risk Factors for an ovulation Diagnosed at 50 Days in Milk in Dairy Cows
Bibliographic record
Abstract
The objectives of this observational study were to determine the optimal progesteronemia threshold for defining anovulation at 50 days in milk (DIM) in dairy cows and to identify risk factors for this condition.A total of 3,776 cows from 100 Holstein dairy herds were enrolled in this cow-level study.During farm visits, cows were bled at 1-14DIM to quantify ketonemia and glycemia, examined at 30-43 DIM to diagnose purulent vaginal discharge, cytological endometritis, and leukocyte esterase endometritis, and were bled at a 14d interval to quantify progesteronemia.Multiple progesteronemia thresholds were tested to identify the one providing the highest sum of sensitivity and specificity to predict the pregnancy status at first service.The optimal threshold found for defining anovulation at 50DIM was ≤0.90 ng/mL.The final model for risk factors included parity group, season of calving, cytological endometritis, hyperketonemia, hypoglycemia, and the two-way interaction term of hyperketonemia and hypoglycemia.Overall, these results suggest that a progesteronemia threshold of ≤0.9ng/mL could be used to define anovulation at 50 days in milk in dairy cows.
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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 | 0.003 |
| 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".