Effects of distillers‘ dried grains with solubles on behavior of sows kept in a group-housed system with electronic sow feeders or individual stalls
Bibliographic record
Abstract
Li, Y. Z., Phillips, C. E., Wang, L. H., Xie, X. L., Baidoo, S. K., Shurson, G. C. and Johnston, L. J. 2013. Effects of distillers’ dried grains with solubles on behavior of sows kept in a group-housed system with electronic sow feeders or individual stalls. Can. J. Anim. Sci. 93: 57–66. A study was conducted to investigate the effects of diets that contained distillers’ dried grains with solubles (DDGS) on stereotypic behaviors of gestating sows housed in stalls and aggression in a group-housed system. Sows were fed corn–soybean-based control (CON) or treatment (DDGS) diets starting from their previous breeding cycle (40% and 20% DDGS as-fed basis during gestation and lactation, respectively). Group-housed sows were mixed in pens with an electronic sow feeder within 1 wk after mating. Behaviors of focal sows (n=27 in stalls, n=40 in pens) were video-recorded for a period of 24 h between 4 and 8 d after mating. Salivary cortisol levels were measured on 32 focal sows (n=16 in stalls, n=16 in pens) during the week before mating (week 0), 1 wk and 12 wk after mating. In pens, DDGS sows fought for longer periods (P=0.05), tended to fight more frequently (P=0.06), and had greater cortisol concentrations (P<0.001) at mixing compared with CON sows. In stalls, DDGS sows spent more time resting (P=0.02), less time performing stereotypies (P=0.05), and had lower cortisol concentrations (P=0.03) in week 12 compared with CON sows. These results indicate that DDGS diets may compromise the welfare of sows in pens, but improve the welfare of sows in stalls.
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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 | 0.001 |
| 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".