Role of triptorelin and single fixed-time artificial insemination on productive and reproductive performance of hyperprolific sows
Bibliographic record
Abstract
Single fixed-time artificial insemination (SFTAI) provides a streamlined approach to improving reproductive management. We evaluated the impact of incorporating triptorelin acetate (GnRH agonist) into a SFTAI protocol on a commercial farm. Hyperprolific sows not in estrus by day 4 post-weaning were randomly assigned to two groups. Group-1 (G1; n = 243) received no triptorelin treatment and daily post-cervical artificial inseminations (PCAI) based on estrus detection (2.59±0.034 inseminations/sow). Group-2 (G2; n = 249) received a single intravaginal dose of triptorelin (0.2 mg) at 96 ± 2 hours post-weaning, then one PCAI 22 ± 2 hours later. No significant differences ( P >0.05) between groups in conception rate (G1: 98.8%; G2: 97.6%), farrowing rate (G1:95.1%; G2: 94.4%) or litter characteristics (total born, live-, stillborn and mummified piglets). Both groups showed similar delivery batch durations ( P =0.414). Distribution of deliveries during the delivery period was similar ( P =0.455). Induction of labor was need more frequently in G1 ( P <0.001). G2 had a higher proportion of sows with shorter gestations (112-115 days: 166/235, 70.6%) compared to G1 (112-115 days: 82/231; 35.5%, P<0.001). A significantly higher proportion of G2 piglets received longer lactation (27 - 33 days) compared to G1 (2210/3023=73.1% vs 2774/4395=63.1%; P = 0.032). G1 had a higher proportion of low-weight piglets (≤4.0 kg; 716/43950=16.3% vs.435/3023= 14.4%; while G2 had more heavy piglets (≥6.5kg; 1228/3023=40.5% vs.1675/4395= 38.1%) ( P =0.027). Observed differences in lactation length could be responsible for these weaning weight differences, rather than triptorelin treatment itself. This protocol did not worsen productive and reproductive performances.
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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 | 0.001 |
| 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".