Nutritional Content of Sliced Bread Available in Quebec, Canada: Focus on Sodium and Fibre Content
Bibliographic record
Abstract
Bread is a highly consumed food and an important source of nutrients in the diet of Canadians, underlining the need to improve its nutritional quality. The Food Quality Observatory (Observatory) aimed to evaluate the nutritional value of the sliced bread products available in Quebec (Canada), according to their grain type and main flour. Analyses included comparing the bread's sodium content to Health Canada's daily values (DV) and sodium voluntary targets, comparing the bread's fibre content thresholds with the source of fibre mentioned, and assessing whether the main flour was associated with the nutrient content. The nutritional values of 294 sliced breads available in Quebec were merged with sales data (from October 2016 to October 2017), with 262 products successfully cross-referenced. The results showed that 64% of the breads purchased were 'low' in fibre (i.e., below 2 g per two slices), while 47% were 'high' in sodium (i.e., above 15% DV per two slices). Attention should be paid to 100% refined grain bread and to bread with refined flour as the main flour, since they are great sellers, while showing a less favourable nutrient content. This study shows that there is room for improvement in the nutritional content of Quebec's bread offer, particularly regarding sodium and fibre content.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".