Effect of low-oil corn dried distillers’ grains with solubles on growth performance, carcass traits and beef fatty acid profile of feedlot cattle
Bibliographic record
Abstract
He, M. L., Xu, L., Yang, W. Z., Gibb, D. and McAllister, T. A. 2014. Effect of low-oil corn dried distillers’ grains with solubles on growth performance, carcass traits and beef fatty acid profile of feedlot cattle. Can. J. Anim. Sci. 94: 343–347. The objective of this study was to investigate the effects of dietary inclusion of low-oil corn dried distillers’ grains with solubles (LO-DDGS) on growth, carcass traits and beef fatty acids profiles of finishing feedlot cattle. One hundred and eighty British crossbred steers (450±28.5 kg; six pens/treatment) were offered barley grain-barley silage as the control diet with LO-DDGS replacing barley grain at 200 and 300 g kg−1 dry matter basis in treatment diets. Compared with control, LO-DDGS at 200 g kg−1 did not affect growth performance or carcass traits, whereas at 300 g kg−1 it decreased (P<0.05) gain:feed, but increased (P<0.05) levels of desirable fatty acids in beef. LO-DDGS can replace 200 g kg−1 barley grain in finishing feedlot diets without undesirable impacts on growth performance or carcass traits.
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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 | 0.000 |
| 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".