102: Validation of a Vitamin D Dietary Intake Screening Questionnaire in Young Children
Bibliographic record
Abstract
Vitamin D dietary intake is an important predictor of vitamin D status in young children; however, measuring vitamin D intake in early childhood is challenging in the pediatric office setting. To determine how well a simple, 1 min parent completed, dietary screening questionnaire (DSQ) completed in the pediatric office setting correlates with a detailed prospective three-day estimated food record (EFR) in measuring daily dietary vitamin D intake in children one to five years of age and to examine the correlation between the DSQ and EFR for assessing milk and vitamin D supplement intake. The mean vitamin D dietary intake values derived from the DSQ and EFR were compared using a paired two-tailed Student's t test and Spearman correlation coefficient. Seventy-four children consented to participate in this study and were included in the analysis. Mean age was 34 months, 60% were male, 55% were European, and median zBMI was 0.12. The mean calorie intake according to the EFR was 1257 calories. The mean vitamin D dietary intake according to the DSQ was 493 (SD 399) IU and EFR was 443 (SD 389) IU. Paired student t-test revealed a P value of 0.37. The Spearman correlation was 0.47 for total vitamin D intake, 0.56 for vitamin D supplement intake and 0.69 for cow's milk intake. A 1 min DSQ completed in the pediatric office setting, including cow's milk and supplement use correlates well with a detailed EFR. Future studies include determining whether the DSQ predicts 25-hydroxyvitmain D.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".