Short Communication: Prepartal Concentration of Estradiol-17β in Heifers with Stillborn Calves
Bibliographic record
Abstract
This study was conducted to investigate hormonal imbalances preceding stillbirths and dystocia in primiparous heifers. The study was conducted between 2003 and 2004 on a German dairy farm, including 433 heifers. Starting 3 wk before calving, a weekly blood sample was collected. At calving, another blood sample was obtained, and the calving ease (grade 0 = unassisted to grade 2 = heavy pull with mechanical calf puller), sex, birth weight, as well as vitality status (stillborn, alive) of the calf were recorded. The blood serum was analyzed for estradiol-17beta and progesterone concentration. At parturition, the measured estradiol-17beta concentration was greater in heifers delivering bulls than in those with female calves and was increasing with greater birth weight of the calf and increasing calving difficulty score. Already 2 wk before calving, the serum estradiol-17beta concentration was significantly smaller in heifers with stillborn than live calves. On the other hand, the progesterone concentration was greater 2 wk before calving in heifers with stillborn calves, but it was unaffected by the birth weight or sex of the calf or the calving difficulty score. Stillborn and live calves did not differ in birth weight or pregnancy duration. The smaller estradiol-17beta concentrations of the heifers with stillborn calves could indicate an abnormality of the placenta or an abnormality of hormonal signals from the calf to the placenta in the weeks before the calving.
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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 | 0.000 | 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 | 0.000 | 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) | 0.002 | 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".