Reliability of self-reported sun exposure in Canadian women and estimation of lifetime exposure to vitamin D from sun and diet
Bibliographic record
Abstract
OBJECTIVE: To assess the inter-method reliability of the Ovarian Cancer in Alberta (OVAL) survey developed to estimate adult vitamin D exposure from sun and diet for every tenth year, against the longer Geraldton Skin Cancer Prevention Survey (the assumed 'gold standard'). We also estimated total vitamin D exposure using the OVAL survey. DESIGN: A randomized crossover design to assess the inter-method reliability of sun exposure (OVAL v. Geraldton survey), using intra-class correlation and estimated total vitamin D exposure from sun and diet. SETTING: Calgary, Alberta, Canada. SUBJECTS: Randomly selected women (n 90) aged 40-79 years. RESULTS: The average lifetime sun exposure of 13,913 h (average 411 h/year) from the Geraldton survey was not significantly different from the 13,034 h (average 385 h/year) from the OVAL survey for periods with sufficient UV radiation to stimulate vitamin D production. The intra-class correlation coefficient for average lifetime sun exposure was 0.77 (95% CI 0.69, 0.86); the annual average was 0.60 (95% CI 0.47, 0.74). Estimated vitamin D from diet and supplements increased with age. CONCLUSIONS: Our OVAL survey reliably estimated adult sun exposure relative to the Geraldton survey, suggesting that assessing sun exposure every tenth year is a reliable and efficient method for estimating sun contributions to lifetime vitamin D exposure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 |
| 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 | 0.001 |
| 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".