Follicular dynamics and in vitro embryo production after repeated superovulation with FSH-P in Simmental heifers.
Bibliographic record
Abstract
Ultrasound transvaginal ovum pick-up was performed in 6 Simmental heifers aged between 14 and 18 months. Heifers were synchronized with PGF2 and stimulated with pFSH, twice a day during two days (Folltropinr ; ; ; ; ; -V, Vetrepharm Inc., London, Canada, a total dose: 200 mg NIH-FSH-P1). Dominant follicle presence was registered ultrasonically on the beginning of superovulatory treatment and follicular dynamic was followed-up 12, 24 and 48 hours after the first pFSH injection. Follicles were classified according to diameter in 4 categories: 2-5 mm ; 6-9 mm ; 10-14 mm and 15 mm. OPU was performed 48 hours after the last FSH injection and procedure was repeated every 14 days during 2 months (a total of 4 aspirations per heifer). Retrieved oocytes were classified in four quality categories. Grade 1 and grade 2 oocytes were matured, fertilized and cultured in vitro in SOFaaBSA medium till the Day 10. Cultured embryos were evaluated morphologically according to IETS standards. Presence of dominant follicle, registered in 10 heifers, did not affect follicular dynamics after repeated superovulation treatments. The mean number of 4 diameter categories follicles did not show significant differences between repeated superovulation treatments. The mean number of grade 1 and grade 2 categories oocytes was 5.67 0.89. The mean number of 3rd and 4th category oocytes were: 1.37 0.38, 0.25 0.11, respectively. In vitro culture results were: 82.13% cleavage rate on Day 2, 43.14% of morula/blastocysts on Day 7 and 33.08% of hatched blastocysts on Day 10. The results show that the repeated FSH stimulation prior to ovum pick-up does not affect the follicular dynamic and developmental competence of bovine oocytes in Simmental heifers.
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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 | 0.000 |
| 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) | 0.001 | 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".