Assessment of Phenolic Compound Intake from Plant-Derived Products in Adolescents from Ontario, Canada
Bibliographic record
Abstract
Purpose: To better understand which plant-derived products contribute to the usual daily total polyphenol content (TPC) intake of Canadian adolescents. Methods: A convenience sample from 2 southwestern Ontario high schools was obtained (n = 108). Students of all gender and ethnicity were invited to participate if they were enrolled in grades 9–12 and were between the ages of 13 and 18 years. To measure the usual intake of TPC found in fruits, vegetables, fruit juices, nuts and legumes, tea, and coffee and coffee-based beverages, participants completed a food frequency questionnaire. TPC of the tea, coffee and coffee-based beverages, and fruit juices were determined spectrophotometrically, and the TPC of all other food items were calculated using the Phenol-Explorer Database. Results: Participants’ median consumption of TPC was 974 mg/day (25th, 75th percentile; 559, 2161, respectively). Fruit contributed 69% to TPC intake with 24% from vegetables; 3% from juice; 2% from tea, coffee, and coffee-based beverages; and 0% from nuts and pulses. No sex differences were found. Conclusion: The results of this exploratory study suggest that fruit is the major contributor to the daily TPC intake of adolescents in Ontario, Canada; however, a larger-scale study is warranted to confirm these findings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".