Comparison in dietary patterns derived for the Canadian Newfoundland and Labrador population through two time-separated studies
Bibliographic record
Abstract
BACKGROUND: While a dietary pattern is often believed to be stable in a population, there is limited research assessing its stability over time. The objective of this study is to explore and compare major dietary patterns derived for the Canadian subpopulation residing in Newfoundland and Labrador (NL), through two time-separated studies using an identical method. METHODS: In this study, we derived and compared the major dietary patterns derived from two independent studies in the NL adult population. The first study was based on the healthy controls from a large population-based case-control study (CCS) in 2005. The second was from a food-frequency questionnaire validation project (FFQVP) conducted in 2012. In both studies, participants were recruited in the same manner and dietary information was collected by an identical self-administered food-frequency questionnaire (FFQ). Exploratory common factor analysis was conducted to identify major dietary patterns. A comparison was conducted between the two study populations. RESULTS: Four major dietary patterns were identified: Meat, Vegetables/fruits, Fish, and Grains explaining 22%, 20%, 12% and 9% variance respectively, with a total variance of 63%. Three major dietary patterns were derived for the controls of the CCS: Meat, Plant-based diet, and Fish explaining 24%, 20%, and 10% variance respectively, with a total variance of 54%. As the Plant-based diet pattern derived for the CCS was a combination of the Vegetables/fruits and Grains patterns derived for the FFQVP, no considerable difference in dietary patterns was found between the two studies. CONCLUSION: A comparison between two time-separated studies suggests that dietary patterns of the NL adult population have remained reasonably stable over almost a decade.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".