Determining What Constitutes Nutritional Risk in Toddlers (18-35 months): First Steps in the Development of Toddler NutriSTEP (Registered Trademark)
Bibliographic record
Abstract
This research is part of an ongoing program, Nutrition Screening Tool for Every Preschooler (NutriSTEP®). NutriSTEP® is a valid and reliable 17-item, parent-administered, questionnaire for nutritional risk in preschoolers (3-5 years of age). Due to an expressed need across Canada, the specific objective of this research was to create a draft toddler (18-35 month) NutriSTEP®. Based on results from a comprehensive literature review, focus groups (n=6) with 48 parents of toddlers, and input from 13 pediatric nutrition experts, many questions from the original preschooler NutriSTEP® questionnaire were refined or removed, and novel questions were added. Basic changes included combining separate fruit and vegetable intake questions, and adding breast milk and formula as examples of dairy products. In conclusion, a 19 item Toddler NutriSTEP® was created to reflect the differences in nutritional risk between preschoolers and toddlers. Next steps in the development process include refinement, test-retest reliability and criterion validation.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".