Effect of wheat distillers' grains with solubles and a feed flavour on performance and carcass traits of growing-finishing pigs fed wheat and canola meal based diets
Bibliographic record
Abstract
Forty-eight crossbred pigs were assigned to one of six dietary treatments in a 6 x 2 (treatment x sex) factorial arrangement. Diets were based on wheat and canola meal and were formulated to contain 0%, 4.9%, 9.7%, 14.6% or 19.4% wheat distillers' dried grains with solubles (DDGS) during the growing period and 0%, 4.0%, 8.1%, 12.1% and 16.1% wheat DDGS during the finishing period. The addition of wheat DDGS was made at the expense of both wheat and canola meal. A feed flavour was added to the diet in which wheat DDGS supplied 100% of the supplementary protein. Over the entire experimental period (21.5-112.2 kg), increasing the level of wheat DDGS resulted in a linear decrease in weight gain and feed conversion ratio. Feed intake was linearly reduced by inclusion of wheat DDGS during the growing period (21.5-57.4 kg) but not the finishing period (57.4-112.2 kg). Increasing the level of wheat DDGS in the diet resulted in a linear decline in carcass value index and lean yield while loin fat linearly increased. The addition of a flavour to the diet in which DDGS supplied 100% of the supplementary protein had no effect on 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".