Influence of Gonadotrophin‐Induced First Oestrus on Gilt Fertility
Bibliographic record
Abstract
The aim of this study was to determine the association between the oestrous response of pre-pubertal gilts to gonadotrophin injection or boar exposure and their subsequent farrowing rate and litter size. At 154 days of age, randomly selected pre-pubertal gilts received an intramuscular injection of 400 IU equine chorionic gonadotrophin plus 200 IU human chorionic gonadotrophin (PG600(®) ; Merck Animal Health; n = 181). From the remaining pool of animals not treated with hormones, the first gilts showing signs of oestrus were selected to act as controls (n = 201). Boar exposure began at 155 days of age for both groups, and gilts were bred at a weight of approximately 130 kg. Comparisons were made between PG600(®) -treated gilts exhibiting oestrus or not within 7 days post-injection (early and late responders, respectively) and control gilts exhibiting oestrus or not within 30 days after beginning of boar exposure (select and non-select control gilts, respectively). By 162 days, oestrus was detected in 67.5% of PG600(®) -treated gilts compared with 5.7% of control gilts (p < 0.0001). The proportion of animals observed in oestrus at least three times before breeding was greater for select control gilts compared with early and late responder PG600(®) -treated gilts (p ≤ 0.001). There were no significant differences in farrowing rate and litter size between the four treatment groups. These data indicate that PG600(®) is an effective tool to induce an earlier oestrus in gilts, that subsequent farrowing rate and born alive litter size compare favourably to that of select gilts and that gilts failing to respond promptly to hormonal stimulation do not exhibit compromised fertility.
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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".