Bibliographic record
Abstract
Prolificacy has been defined as the number of viable piglets produced per year or per breeding lifetime.Prolificacy is influenced by age at first successful mating, ovulation rate and embryo survival at each mating, number of live born, viable pigs and the sow's ability to be successfully remated at regular intervals.It is concluded that under normal conditions of feeding and management nutrition will have a minimal influence on gilt prolificacy.However, to gain the advantages of a slightly younger age at puberty, maximal ovulation rate and an adequate fat cover (if only to ensure against subsequent poor management), gilts should be fed ad libitum up to the time of mating.Long-term performance is best served by minimizing fluctuations in live weight and fat reserves, so avoiding extremes of body condition and subsequent poor performance.This is achieved by small controlled increases in sow body weight during pregnancy and feeding to appetite for restricted periods each day during lactation.Assuming the sow has not achieved a very poor condition during lactation, feeding level during pregnancy will have little effect on numbers of piglets born, and only a limited influence on piglet birthweights.The conclusion that piglet birth weights will be influenced more by total pregnancy feed intake than pattern of feed distribution is unchallenged.Lactation feed intake is shown to have marked effects on the post-weaning performance, low-level feeding leading to an extension of the remating interval and possibly increasing embryo mortality.No benefit of high-level feeding after weaning is demonstrable, except possibly in primiparous sows or sows having suffered an extreme loss of liveweight and body condition during the previous lactation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".