Direct Determinations of the Fatty Acid Composition of a Typical Canadian Dietary Intake and Omega‐3 Enriched Nutraceutical and Functional Food Based Dietary Intakes
Bibliographic record
Abstract
North Americans consume low amounts of eicosapentaenoic acid (20:5n‐3, EPA) and docosahexaenoic acid (22:6n‐3, DHA). We investigated increasing EPA+DHA in daily meals by nutraceutical, functional food and whole food strategies including financial cost. Daily meals were similar in macronutrient and energy composition and included; typical Canadian diet (TCD), nutraceutical fish oil capsules addition (NFO), EPA+DHA enriched functional foods substitution (EDF), and EPA+DHA functional foods with flax products and fish (FFF). Homogenates of each daily meal were prepared after cooking. Direct quantitation of fatty acid composition was determined by gas chromatography in triplicate. Food was purchased during a single visit to a supermarket grocery store. The EPA+DHA content of each daily diet was: TCD, 0.08 ± 0.06 g; NFO, 0.97 ± 0.03 g; EDF, 0.63 ± 0.06 g; FFF, 3.45 ± 0.42 g. The total cost of each diet differed by $1.58 with TCD being the least and FFF being the most expensive. In terms of cost per g of EPA+DHA in the present study, fish oil capsules was the least expensive followed closely by salmon ($0.52/g vs. $0.58/g EPA+DHA, respectively). The present study suggests that EPA+DHA daily intakes can be increased significantly by nutraceutical, functional and whole food strategies. These increases can be achieved with minor increases in cost although certain strategies are more cost effective than others.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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 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".