role of prostaglandin F2α on ovulation and LH release in cows
Bibliographic record
Abstract
This study aimed to evaluate the role of prostaglandin F2α (PGF) on ovulation. In Experiment 1, cows were randomly allocated to two treatments to receive 150 μg of d-Cloprostenol (PGF Group, n = 12) or 2 mL of NaCl 0.9% (Control Group, n = 11) and CIDRs, were removed 4 days later. No cow ovulated in Control and PGF groups. In Experiment 2, cows were randomly separated into two experimental groups to receive 4 injections of 150 μg of d-Cloprostenol (n = 9) or 2 mL of NaCL 0.9% (n = 9). In this experiment, ovulation was not observed in any cows. In Experiment 3, ovariectomized cows receive three injections of 300μg of PGF analog (PGF Group, n = 5), 100μg of Lecirelin (GnRH Group, n = 5) or 2 mL of PBS (Control Group, n = 4). The LH concentration was higher (P <0.0001) in cows from the GnRH group than in the PGF and Control groups. In experiment 4, cows with preovulatory follicles (>11.5 mm) were treated with Saline (Control Group, n = 6); Lecirelin (GnRH Group, n = 7) or Cloprostenol Sodium (PGF Group, n = 6). There was a significant increase in the vascular area of follicles from 0 to 24 h in GnRH and PGF treatments. In conclusion, PGF was not able to induce ovulation in cows with high or low plasma progesterone concentration. Additionally, PGF alone was not able to induce LH release and follicle luteinization, but increased follicular vascularization.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".