Impact of gonadotropin-releasing hormone administration at the time of artificial insemination on conception risk and its association with estrous expression
Bibliographic record
Abstract
Cows with reduced estrous expression have compromised fertility. The aim of this study was to determine whether the administration of GnRH at the time of artificial insemination (AI) would affect ovulation rates and the fertility of animals expressing estrous behavior of lesser intensity. Cows were enrolled at the time of estrus from 3 farms (n = 2,607 estrus events; farm A: 1,507, farm B: 429, farm C: 671) and randomly assigned to receive GnRH at AI or not (control). The intensity of estrous expression, monitored through leg-mounted activity monitors, was determined using the maximum activity during estrus; estrous expression was categorized as greater or lower relative to the farm median. On farm A, cows were assessed at alert, and 24 h, 48 h, and 7 d post-alert for ovulation using ultrasonography. Pregnancy per AI was confirmed at 35 ± 7 d post-estrus for cows that were inseminated. Differences between treatments were tested using the GLIMMIX procedure of SAS. Treatment with GnRH at the time of AI increased pregnancy per AI (41.3 ± 1.6 vs. 35.7 ± 1.7%). An interaction between treatment and estrous expression on pregnancy per AI was found. Control cows with greater estrous expression had greater pregnancy per AI than those with lesser expression, whereas GnRH administration increased pregnancy per AI for cows with lesser estrous expression but not those with greater expression (GnRH, greater intensity: 43.5 ± 2.1; GnRH, lesser intensity: 37.8 ± 2.2; control, greater intensity: 42.6 ± 2.2; control, lesser intensity: 31.0 ± 2.2%). A higher proportion of cows with greater estrous expression that were administered GnRH at AI were found to ovulate by 48 h and 7 d post-estrus; however, ovulation of cows with lesser estrous expression was unaffected by GnRH administration. In conclusion, fertility of cows with reduced estrous expression may be increased using GnRH at the time of AI; however, increased ovulation rates do not seem to be the direct mechanism behind this relationship.
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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 | 0.001 |
| 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".