Effects of feeding or abomasal infusion of canola oil in Holstein cows 1. Nutrient digestion and milk composition
Bibliographic record
Abstract
We determined the effects of feeding canola oil or infusing it into the abomasum on rumen fermentation, nutrient digestibility, duodenal flows of fatty acids, and milk composition in Holstein cows. Five ruminally and duodenally cannulated Holstein cows in late lactation were used in a 3 x 5 incomplete Latin square design. Treatments were 1) CONTROL: basal diet (CON), 2) CONTROL+supplementation of canola oil at 1 kg/d in the feed (FED), and 3) CONTROL+abomasal infusion of canola oil at 1 kg/d (INF). Compared with CON, feed intake, ruminal fermentation characteristics, ruminal and total tract digestibilities of nutrients were not significantly affected by FED treatment but duodenal flows and milk concentrations of fatty acids (FA) such as trans-11 18:1 and cis-9 trans-11 18:2 (conjugated linoleic acid, CLA) were increased. In contrast to the effects of FED, INF reduced feed intake, total VFA production, intestinal flows of nutrients, FA digestibility and yields of milk and milk fat. Both FED and INF significantly reduced the proportions of saturated and medium-chain FA, and increased cis 18:1 in milk. Concentrations of 18:2n-6 and 18:3n-3 in milk were increased nearly 2-fold with INF relative to CON. Dietary or postruminal supplementation of canola oil to late-lactation cows reduced saturated FA and increased unsaturated C18 in milk but nutrient digestion was adversely affected with abomasal infusion of canola oil.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".