19 THE EFFECT OF PROGESTERONE ON FOLLICULAR DEVELOPMENT AND PREGNANCY RATE IN BEEF CATTLE
Bibliographic record
Abstract
The objective was to determine the effect of the level of progesterone (P4) during the ovulatory wave on fertility. Low v . high progesterone concentrations which were expected to result in high v . low LH pulse-frequency were compared. Lactating, postpartum beef cows ( n = 69) at random stages of the estrous cycle were given cloprostenol (PGF; Schering-Plough Animal Health, Pointe-Claire, QC, Canada) twice at an 11-day interval to synchronize ovulation (Day 0 = day of 2nd PGF). Cows were given 1.5 mg estradiol benzoate on Day 10 (7 days after expected ovulation). On Day 10, the Low-P4 group was given PGF and an intravaginal CueMate (Bioniche Animal Health, Belleville, ON, Canada) containing one P4 pod (expected to achieve a P4 plasma level of 1 ng mL–1). The High-P4 group also received a CueMate with one pod on Day 10, but no PGF was administered (i.e., cows were allowed to retain their CL for 4 days after expected emergence of the estradiol-induced wave). On Day 18, CueMates were removed and PGF was administered to both groups. Fifty-four to 56 h later, all animals received 12.5 mg of Lutropin-V (Bioniche) IM and were timed AI (TAI). Dominant follicle diameter was measured on Day 18 and at the time of AI. Pregnancy diagnosis was done by ultrasonography 27 days after AI to compare fertility between groups. Follicle diameter data were analyzed by Student's t -test and pregnancy rate data were compared by the chi-square test. The dominant follicle in the Low-P4 group was larger ( P < 0.05) than in the high-P4 group on the day of the CueMate removal (Day 18) and on the day of the TAI (11.8 ± 0.4 and 13.7 ± 0.5 v . 13.3 ± 0.6 and 15.3 ± 0.6 in the High-P4 and Low-P4 groups, respectively). Pregnancy rate was similar ( P = 0.16) between the groups (High-P4: 55.6% (20/36) and Low-P4: 44.4% (16/33)); however, a larger study is in progress to confirm these results. To conclude, Low-P4 resulted in a larger dominant follicle without any apparent effect on pregnancy rate. The project was funded by Saskatchewan ADF and NSERC. L. Pfeifer is funded through a CAPES scholarship. We acknowledge Schering-Plough and Bioniche for donation of pharmaceuticals .
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How this classification was reachedexpand
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 | 0.002 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".