Response of Layers to Dietary Flaxseed According to Body Weight Classification at Maturity
Bibliographic record
Abstract
A trial was conducted with layers weight-sorted into small (1200-1285 g), medium 1 (1360-1395 g), medium 2 (1430-1460 g), or heavy (1555-1600 g) body weight classifications at 18 wk and fed 0, 10, or 20% flaxseed. Regardless of weight classification, feeding 20% flaxseed resulted in inadequate weight gain, reduced egg production, and increased feed intake. It was hypothesized that smaller birds would be less able to increase their feed intake in response to flax (due to reduced nutrient digestibility or antinutrients) and so show more severe loss in egg production. This situation did not occur, since all birds adjusted their intake to a comparable level. It is concluded that lower egg production seen in birds fed high levels of flaxseed may be due to the presence of antinutrients or reduced AMEn of the diet.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".