Recent advances in the superovulation in cattle
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it