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
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it