<i>Dietary reference intakes:</i>A comparison with the Nova Scotia Nutrition Survey
Bibliographic record
Abstract
The purpose of this study was to compare the newly released dietary reference intakes with the 1990 Nova Scotia Nutrition Survey and identify characteristics that influence compatibility with these new recommendations. For each of 17 nutrient recommendations, we calculated the proportion of participants who consumed intakes within the recommended range. We constructed a score reflecting overall compatibility between the new recommendations and the Nova Scotia Nutrition Survey data. Using this score as the dependent variable, we conducted multivariate regression analysis to evaluate the importance of demographic and behavioural factors for compatibility with the dietary reference intakes. Results indicate that compatibility with the dietary reference intakes was poor among Nova Scotians, particularly for magnesium, vitamins C and E, and macronutrients. Compatibility was lower among females than among males, and differed independently by age, body mass index, socioeconomic factors, smoking status, and alcohol consumption. Dietary intervention is needed in Nova Scotia. Reduced fat intake and increased intake of specific vitamins should be promoted. We recommend that nutrition education campaigns coinciding with the introduction of the dietary reference intakes in Nova Scotia target younger people, those of lower socioeconomic background, smokers, and those who are obese.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".