Associations between maternal characteristics and health, survival, and performance of dairy heifers from birth through first lactation
Bibliographic record
Abstract
The objective of this study was to investigate whether health, survival, and performance of dairy heifers from birth through first lactation are associated with parity and health status of their dams. Holstein heifers (n = 1,811) derived from artificial insemination were categorized as (1) daughters of primiparous cows that, consequently, were nonlactating heifers during gestation (Prim-NoL; n = 787); (2) daughters of multiparous cows that did not have any clinical diseases in the previous lactation (Mult-NoCD; n = 638); and (3) daughters of multiparous cows that had at least one clinical disease in the previous lactation (Mult-CD; n = 386). Clinical diseases of the multiparous dams included retained placenta, metritis, mastitis, lameness, and digestive and respiratory problems. Data collected for evaluation of daughters included genotypic and phenotypic characteristics at birth, morbidity, reproductive performance, and culling from birth through 305 d in milk of first lactation. Orthogonal contrasts were used to evaluate the effect of the parity of the dam (Prim-NoL vs. Mult-NoCD + Mult-CD) and the effect of clinical disease occurrence in the previous lactation among multiparous dams (Mult-NoCD vs. Mult-CD). Compared with daughters of multiparous cows, daughters of Prim-NoL were lighter at birth (36 vs. 41 kg), had greater genetic merit for production traits (e.g., genomic estimated breeding value for milk yield: 875 vs. 746 kg), were less likely to leave the herd (17 vs. 28%) and to lose pregnancy as a heifer (9 vs. 14%), calved earlier (703 vs. 711 d old), were less likely to have clinical diseases as a first lactation cow (30 vs. 37%), and had reduced performance in the first lactation when considering their genetic merit (e.g., 305-d yield of energy-corrected milk: 11,270 vs. 11,539 kg). Compared with daughters of Mult-NoCD, daughters of Mult-CD were less likely to have digestive problems as a heifer (17 vs. 27%) and clinical disease as a first lactation cow (32 vs. 42%), but were also more likely to leave the herd as a heifer (32 vs. 25%) even though genetic merit for production traits were similar (e.g., genomic estimated breeding value for milk: 744 vs. 749 kg). In conclusion, both parity and health status of the dam in the previous lactation were associated with morbidity, survival, and performance of their daughters from birth through 305 d in milk of the first lactation and might represent factors affecting developmental programming of dairy heifers in utero.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".