Apparent metabolizable energy values of <i>n</i>-6 and <i>n</i>-3 rich lipid sources for laying hens
Bibliographic record
Abstract
The objective of this research was to evaluate the nitrogen-corrected apparent metabolizable energy (AMEn) balance of the following lipid sources: soybean oil, sunflower oil, linseed oil, and fish oil. Two hundred eighty 24-wk-old laying hens of the Hysex White were used. The experimental diets consisted of a basal diet (reference group), basal diet + 10% soybean oil addition (group 1), basal diet + 10% sunflower oil addition (group 2), basal diet + 10% linseed oil addition (group 3), and basal diet + 10% fish oil addition (group 4), distributed in a completely randomized design with seven replicates and eight birds per experimental unit. The metabolic assay was performed by the total excreta collection method. The AMEn values found in the natural material were 9 334 kcal kg−1 for soybean oil, 10 533 kcal kg−1 for sunflower oil, 10 928 kcal kg−1 for linseed oil, and 9 005 kcal kg−1 for fish oil. The AMEn were different among the lipid sources. Sunflower oil and linseed oil had higher AMEn compared with soybean oil and fish oil (P < 0.05). The AMEn of the lipid sources of plant origin had higher values than the gross energy. The fatty acid profile of each lipid source was presented in this work. Thus, it is important to have individual nutritional information for each type of oil for laying hens, making it possible to formulate more appropriate and accurate feed.
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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".