Providing periodic exercise to stall-housed gestating sows influences only the total number of live-born piglets in older parity sows
Bibliographic record
Abstract
The 2014 Canadian Pig Code of Practice includes a recommendation to provide stall-housed gestating pigs with periodic exercise. The objective of this study was to evaluate the effects of periodic exercise on sow performance and placental and piglet characteristics. Sows ( n = 180) were assigned to one of three gestation treatments: stall-housed sows (Control: C), stall-housed sows given weekly exercise (Exercise: E—10 min of walking per week), and group-housed sows (Group: G). Sows were distributed among three parity groups: young (parity 0–1), mid (parity 2–4), and old (parity 5–7). Old C sows had a higher number of total born than G sows, and E sows were intermediate; mid G sows had a higher total born than E and C sows ( P = 0.023). Old E and G sows had similar numbers of total live-born piglets, which were higher than in old C sows ( P = 0.033). Periodic exercise did not influence placental and piglet characteristics in the current study. In conclusion, periodic exercise benefited only the reproductive performance of older parity sows, increasing the number of live-born piglets in E and G sows compared to C sows.
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 | 0.000 | 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".