Nutritionally Important Fatty Acids in Hen Egg Yolks from Different Sources
Bibliographic record
Abstract
Egg samples were collected from six different sources across Canada, and the yolks from those samples were analyzed for fatty acid composition using gas chromatography. Three yolk samples were from regularly fed chickens from three different Canadian egg processing plants, and the other three samples were from chickens fed with special diets. The specially fed chicken yolk samples were collected from three different Canadian egg producers. The three egg yolk samples from specially fed chickens had a significantly higher linolenic acid and docosahexaenoic acid content than the three regularly fed chicken yolk samples (P < 0.05). However, the arachidonic acid levels in the regularly fed chicken yolk samples were significantly higher (P < 0.05). In general, there was no significant difference among the three egg sources in each group. There was some variation in the fatty acid levels during different seasons for each source, but the difference was not statistically significant in most cases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".