Recent advances in the superovulation in cattle
Bibliographic record
Abstract
The variability in the superovulatory response continues to be one of the most frustrating problems with embryo transfer in cattle. The removal of LH from pituitary extracts has tended to reduce the variability in response, and several studies involving the use of the purified porcine pituitary extract. Folltropin-V are reviewed. The major source of variability in the superovulatory response in cattle is the status of ovarian follicles at the time of initiation of gonadotrophin treatments. Data support the benefits of initiating gonadotrophin treatments at the time of emergence of a follicular wave. Incorporation of techniques designed to control follicular wave dynamics, such as follicular ablation, or treatment with estradiol/progesterone, have reduced the variability caused by treating cows at different stages of follicular development, and at the same time improved response by taking advantage of endogenous recruitment and selection mechanisms. New protocols offer the convenience of being able to initiate gonadotrophin treatments quickly and at a self-appointed time, without the necessity of estrus detection and without sacrificing response. Methods can be used for repeated superstimulation of donor animals at 25 to 30 day intervals, without regard to estrus detection or stage of the estrous cycle, and without compromising embryo production.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".