Omega-3 Fatty Acid Oil Enhancement of a Protein-Based Recovery Beverage: Sensory Analysis with Athletes
Bibliographic record
Abstract
Essential omega-3 fatty acids must be consumed through the diet to meet the body’s nutrition requirement. Daily-recommended intake of omega-3 fatty acids for adults is 270 milligrams/day. These fatty acids are commonly consumed through fish, but it is known that the United States population at large is not meeting their recommended daily intake. Supplements containing these important acids should be considered to close the gap between recommendations and actual intake. To create a product with these beneficial acids, sensory analysis was conducted to see if non-trained male and female athlete panelists could notice the difference in several key sensory characteristics (appearance, initial taste, color, sweetness, consistency, chocolate flavor, aftertaste, overall quality and overall liking) in a chocolate protein-based recovery beverage. The sensory-neutral oil was added into the beverage and athletes (n=95) were asked to taste the omega-3 and original beverage and rank each characteristic on hedonic and just-about-right scales. Color of the drink, aftertaste, overall quality and overall liking were rated significantly higher for the omega-3 added drink. Overall, the addition of the omega-3 fatty acids improved the beverage in several key attributes and can be added into the final formulation of the product.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".