New approaches to superovulation in the cow
Bibliographic record
Abstract
There is continuing need to simplify bovine superovulation protocols without compromising embryo production. The control of follicular wave emergence and ovulation has facilitated donor management, but the most commonly used treatment, oestradiol, cannot be used in many parts of the world and mechanical removal of the dominant follicle is difficult to apply in the field. Other alternatives include gonadotrophin-releasing hormone (GnRH) or LH, but efficacy in groups of randomly cycling animals is variable. Another alternative is to increase the response to GnRH by inducing a persistent follicle and initiating FSH treatments following GnRH-induced ovulation. The number of transferable embryos following superovulation during the first follicular wave did not differ from that achieved 4 days after oestradiol benzoate and progesterone. To further simplify superovulation, FSH has been administered as a single intramuscular injection. Superovulation of beef donors with a single intramuscular injection of Folltropin-V (Bioniche Animal Health, Belleville, ON, Canada) diluted in a slow-release formulation resulted in embryo production comparable to that obtained using the traditional twice-daily protocol. The single intramuscular injection has the potential to reduce labour and handling and may be useful when handling stress is an impediment to success. These alternatives provide ways of facilitating widespread application of embryo transfer technologies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".