Metabolizable energy values of corn and wheat middlings in broiler chickens
Bibliographic record
Abstract
Two experiments were conducted to evaluate adaptation length (AL) and composition of reference diets on nitrogen (N)-corrected apparent metabolizable energy (AMEn) in 22-d-old broilers. Birds were allocated to nine treatments (n = 6) consisting of wheat – soybean meal (SBM) (reference diet), corn–wheat–SBM, and wheat middlings (WM)–wheat–SBM (exp. 1), or oats–SBM (reference diet), corn–oats–SBM, and WM–oats–SBM (exp. 2) in conjunction with three AL (12, 8, and 4 d) in a factorial arrangement of treatments (3 × 3). Dry matter (DM), N, energy (En) utilization, and AMEn of corn and WM were determined using the difference method. In exp. 1, birds on the WM–wheat–SBM-based diet had the lowest (P < 0.05) DM, N, and En utilization, as well as AMEn compared with the other two diets. Additionally, AMEn for corn was higher (P < 0.05) compared with that of WM. In exp. 2, N utilization in birds on the corn–oats–SBM-based diet was lower (P < 0.05) compared with birds on the oats–SBM-based diet; however, AMEn of corn and WM was not different. In both experiments, AL was not significantly different. Based on these results, the composition of the reference diet could influence AMEn values of corn and WM in 22-d-old broilers.
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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".