Are Pharmacological Interventions Between Conception and Birth Effective in Improving Reproductive Outcomes in North American Swine?
Bibliographic record
Abstract
The objective of this review is to evaluate the effectiveness of using pharmacological compounds on reproductive outcomes, particularly litter size, in North American swine. While the opportunity to improve reproduction in North American pigs exists, numerous hurdles need to be overcome in order to achieve measureable results. In the swine industry, the majority of piglet losses are incurred during pregnancy and around farrowing. Over the last 20 years, a reduction in losses has been achieved through genetic selection and nutritional management; however, these topics are the focus of other reviews. This review will evaluate attempts to improve litter size by reducing losses at various stages of the reproductive process, from the time of conception to the time of farrowing, using pharmacological compounds. Generally, these compounds are used to either alter physiological processes related to fertilization, embryonic attachment or uterine capacity, etc., or to facilitate management aspects of the breeding females such as inducing parturition. Although some of the pharmacological agents reviewed here show some positive effects on improving reproductive parameters, the inconsistent results and associated risks usually outweigh the benefits gained. Thus, at the present time, the use of pharmacological agents to enhance reproduction in North American swine may only be recommended for herds with low fertility and presents an avenue of research that could be further explored.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".