Effects of sunlight hours and hormones on double ovulation, and singleton and twin pregnancies in mares
Bibliographic record
Abstract
Equine twin pregnancies are almost exclusively dizygotic, without the application of advanced reproductive technologies, requiring 2ovulations in 1 estrous cycle. Breeding records were used to determine the effects of sunlight hours, prostaglandin F2α, human chorionicgonadotropin, deslorelin (a gonadotropin releasing hormone agonist), and progesterone and estradiol on double ovulation rates,and singleton and twin pregnancy rates. Breeding records of mares (n = 267) and their estrous cycles (n = 914) were analysed. Doubleovulations occurred in 10.5% (96/914) of estrous cycles. Twin pregnancies were observed in 42.7% (38/89) of mares that had doubleovulations. Overall, per estrous cycle pregnancy rate was 47.2% (405/858) and twin pregnancies was 4.4% (38/858). Double ovulationshad higher (p < 0.001) per cycle singleton pregnancy rate (69.7%; 62/89) than 1-ovulation cycles (44.6%; 343/769). Deslorelinincreased (p < 0.05; OR =1.24 95% CI) double ovulations and human chorionic gonadotropin tended (p = 0.089; OR =1.68; 95%CI) to increase double ovulations. Deslorelin use resulted in an odds ratio of 2.47 for a positive pregnancy (either singleton or twin)diagnosis compared to cycles without deslorelin use. None of the factors examined had a substantial impact on twin pregnancy rates.
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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) | 0.001 | 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".