Reproducibility and validity of a 45 item food-frequency questionnaire for inuit in Greenland
Bibliographic record
Abstract
Since 1993, dietary assessment has been carried out in Greenland as part of recurrent population health surveys.In preparation for the next survey in 2024, 91 participants from the survey in 2018 were selected for a validation study of the Food Frequency Questionnaire (FFQ).The 91 participants were reinterviewed 38-50 months after the first FFQ and invited to complete a food diary.As part of the 2018 survey, blood was analysed for mercury.The food diary was completed by 65 participants.The agreement between the two FFQ interviews was very good for macronutrients and fatty acids (p > 0.20), whereas the calculated intake of mercury was 22% higher in the second FFQ (p = 0.04) due to a higher intake of whale meat and muktuk (whale skin).The agreement between the second FFQ and the food diary was good for local food, imported meat and cakes/ sweets/snacks but fruit and vegetables, dairy products, beverages and added sugar were significantly underreported in the food diary.Food items not included in the FFQ were identified from the food diaries.The correlation between the intake of marine mammals and blood mercury was moderate (Spearman's rho = 0.41-0.50;p < 0.0001).The results will inspire future dietary studies in the circumpolar North.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".