Bridging the Fibre Gap: Using Par-baked bread to Improve Nutritional Awareness and Consumption of Dietary Fibre in Ontario Secondary School Students
Bibliographic record
Abstract
Dietary fibre is a nutrient of concern among Canadians and the discrepancy between recommended and actual consumption is coined the Fibre Gap. Findings from this research aim to bridge this gap. The first phase of this study involved characterizing sensory properties of par-baked breads through projective mapping. Two sets of par-based breads were enriched with dietary fibre from barley, flaxseed, and quinoa. One set of loaves was stored frozen for 8 weeks before re-baking and the other was re-baked within 24 hours. Results showed dietary fibre type influenced sensory properties of the breads more so than frozen storage time. The control loaf without dietary fibre was most liked overall while the flaxseed loaf was most liked for appearance and texture. In phase two, students’ knowledge and consumer attitudes of dietary fibre were assessed. Students’ success in completing the fibre questionnaire varied despite most students having a background in nutrition. This identified a gap knowledge regarding dietary fibre and health. Overall, the information learned will be used to propose strategies to help increase fibre consumption in the Canadian adolescent population.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".