Pregnancy Loss in Dairy Cattle: Relationship of Ultrasound, Blood Pregnancy‐Specific Protein B, Progesterone and Production Variables
Bibliographic record
Abstract
Objectives were to determine associations between percentage pregnancy loss (PPL) in dairy cattle and: (i) pregnancy diagnosis by ultrasonography; (ii) pregnancy diagnosis by serum pregnancy-specific protein B (PSPB) concentrations, with or without serum progesterone concentrations; and (iii) production and environmental factors. This study included 149 822 pregnancy diagnoses conducted over 13 years in Holstein-Friesian cows in Hungarian dairy herds. The following were determined: PPL in cows diagnosed pregnant by transrectal ultrasonography 29-42 days after artificial insemination (AI; n = 11 457); PPL in cows diagnosed pregnant by serum PSPB 29-35 days after AI (n = 138 365); and PPL and its association with serum progesterone concentrations, PSPB and production/environmental variables. The definition of PPL was percentage of cows initially diagnosed pregnant based on ultrasonography or PSPB, but not pregnant when examined by transrectal palpation 60 -70 days after AI. The PPL was lower (p < 0.001) in cows following ultrasonographic vs PSPB diagnosis of pregnancy at 29-35 days (8.1 vs 19.3%, respectively), but was higher in cows following ultrasonographic pregnancy diagnosis on 29-35 vs 36-42 days (8.1 vs 7.1%, respectively, P < 0.05). Furthermore, 72.9% of pregnancies with ultrasound-detected morphological abnormalities resulted in pregnancy loss. As a subset of PSPB data, a fully quantitative PSPB assay was used for 20 430 samples; PPL in cows with a high PSPB concentration (>1.1 ng/ml) was lowest (15.0%), whereas cows with low concentrations of both PSPB and progesterone (0.6-1.1 and <2 ng/ml, respectively) had the highest PPL (76.3%; p < 0.0001). Furthermore, PPL was higher in cows with advanced parity and with high milk production, when ambient temperatures were high, although body condition score (BCS) had no effect on PPL. Finally, there were no significant associations between serum PSPB and environmental temperatures or number of post-partum uterine treatments.
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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".