Effects of feeding ISA brown and Shaver white layer breeders with sources of <i>n</i>-3 fatty acids on hatching egg profiles, apparent embryonic uptake of egg components, and body composition of day-old chicks
Bibliographic record
Abstract
Effects of feeding ISA brown and Shaver white breeders sources of n-3 fatty acids (FA) on egg components, apparent embryonic uptake (AEU) of egg components, and hatching body composition were examined. A total of 240 females and 30 males per each strain were fed either: (1) control (CON); (2) CON + 1% of dried microalgae (DMA), as a source of docosahexaenoic acid; or (3) CON + 2.60% of dry extruded product consisting of full-fat flaxseed (FFF), as a source of α-linolenic acid for 30 d. Eggs were incubated and the residual yolks (RY) sampled at hatch for AEU of dry matter (DM), minerals, and organic matter (OM). Feeding n-3 FA sources reduced the AEU of OM and minerals resulting in a higher ratio of RY to body weight (P = 0.002). Feeding FFF increased body fat and decreased lean in Shaver white hatchlings compared with CON (P < 0.05). The body mineral was reduced by feeding DMA compared with other treatments (P < 0.05). The change in body composition in response to feeding of n-3 sources was associated with the change in AEU of DM, OM, and minerals, not the concentration of these components in the yolk.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".