Net energy of diets containing wheat-corn distillers dried grains with solubles as determined by indirect calorimetry, comparative slaughter, and chemical composition methods1
Bibliographic record
Abstract
The NE content of diets containing wheat-corn distillers dried grains with solubles (wcDDGS; 1:1 ratio) fed to growing pigs was determined using the comparative slaughter (CS), indirect calorimetry (IC), and chemical composition (CH) methods. The experimental diets were a corn-soybean meal control diet (CTRL), CTRL + 15% wcDDGS, and CTRL + 30% wcDDGS. In Exp. 1, 56 barrows (18.5 kg BW) were used to determine the NE value of diets using the CS method. Pigs were initially placed in 8 groups (7/group), based on BW and 1 pig/group was killed at the start of the experiment to obtain baseline body composition. The remaining 48 pigs were housed in pairs and allotted to the 3 diets (n = 8). Pigs had free access to feed and water for a 28-d period, after which 1 pig/pen was slaughtered to determine final body composition. Based on the CS method, NE values of 2,430, 2,427, and 2,429 kcal/kg DM were obtained for diets containing 0%, 15%, and 30% wcDDGS, respectively. In Exp. 2, 18 barrows (20.4 kg BW) were used to determine the NE value of diets using the IC and CH methods. Pigs were individually housed in metabolism crates and fed the 3 diets (n = 6) at 550 kcal ME/kg BW/d for a 16-d period. Feces and urine were collected from d 11 to 16, followed by measurement of O(2) consumption, CO(2) production, and urinary N, over a 36-h period using an IC system. For the IC method, NE values of 2,586, 2,513, and 2,520 kcal/kg DM were obtained for diets containing 0%, 15%, and 30% wcDDGS, respectively, and corresponding values for the CH method were 2,447, 2,451, and 2,368 kcal/kg DM, respectively. The NE values that were obtained with the CS, IC, and CH methods were not different.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".