Net energy content of canola meal fed to growing pigs and effect of experimental methodology on energy values1
Bibliographic record
Abstract
An experiment was conducted to determine the digestible energy (DE), metabolizable energy (ME), and net energy (NE) contents of canola meal (CM) and to investigate the effects of basal diet [corn diet vs. corn-soybean meal (SBM) diet] and methodology (difference method vs. regression method) on energy values of CM. Thirty-six growing barrows (20.8 ± 1.0 kg initial body weight [BW]) were individually housed in metabolism crates and randomly allotted to one of six dietary treatments to give six replicates per treatment. The six experimental diets included a corn diet, a corn-SBM diet, a corn diet with 15 or 30% of CM, and a corn-SBM diet with 15 or 30% of CM. The DE, ME, and NE of CM were determined using the corn diet or the corn-SBM diet as a basal diet. In each basal diet, two additional diets containing 15 or 30% of CM were formulated to compare the determined energy values by the difference method and estimated energy values from the regression method. Feeding level was set at 550 kcal ME/kg BW0.6 per day. Pigs were fed experimental diets for 16 d including 10 d for adaptation and 6 d for total collection of feces and urine. Pigs were then moved into indirect calorimetry chambers to determine 24 h heat production (HP) and 12 h fasting HP. The DE, ME, and NE of CM determined by the difference method were within the 95% confidence intervals estimated for the DE, ME, and NE of CM by the regression method regardless of the basal diets used, which indicates that the difference and regression methods give equivalent DE, ME, and NE of CM. However, when the goodness of fit for the linear model was compared, the r2 of the regression analysis from the corn-SBM diet (0.78) was relatively greater than that from corn diet (0.40). The estimated NE of CM by the prediction equations generated by either the corn diet or corn-SBM diets were 2,096 kcal/kg and 1,960 kcal/kg (as-fed basis), respectively, whereas those values determined by the difference method were 2,233 kcal/kg and 2,106 kcal/kg (as-fed basis), respectively. In conclusion, the NE of CM determined in the current study was, on average, 2,099 kcal/kg (as-fed basis). The difference and regression methods do not give different NE value of CM fed to growing pigs. Although the NE values of CM determined using either the corn diet or the corn-SBM diet were not different, the greater r2 of the regression analysis from the corn-SBM diet than that from the corn diet suggests that the corn-SBM diet is a more appropriate basal diet for NE determination of ingredients.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".