Colostrum production in sows fed different sources of fiber and fat during late gestation
Bibliographic record
Abstract
Krogh, U., Bruun, T. S., Amdi, C., Flummer, C., Poulsen, J. and Theil, P. K. 2015. Colostrum production in sows fed different sources of fiber and fat during late gestation. Can. J. Anim. Sci. 95: 211–223. The objective was to study yield and composition of colostrum and transient milk from 36 second-parity sows fed a standard lactation diet (CON) low in fiber or one of two high-fiber diets based on sugar beet pulp (SBP) or alfalfa meal (ALF), combined with one of three fat sources, palm fatty acid distillate (PFAD), soybean oil (SOYO) or trioctanoate (C8TG) from day 105 of gestation onward. Sows were milked at 0, 12, 24 and 36 h relative to onset of parturition. Jugular vein blood was collected on day 112 of gestation. Plasma acetate content was affected by dietary fiber and fat treatment (P<0.05), indicating altered intermediary metabolism. Colostrum yield, predicted from piglet birth weight, suckling duration and weight gain, was unaffected by dietary treatments (P>0.10). Colostral (24 h) and transient milk dry matter contents were greater in SOYO compared with PFAD and C8TG sows (P<0.05). Colostrum (12 and 24 h) and transient milk lactose contents were greatest in CON-fed sows compared with sows fed ALF or SBP diets (P<0.05). In conclusion, nutrition in late gestation affected the intermediary metabolism and colostrum composition, but did not affect colostrum yield of sows.
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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".