Impact of primary food allergies on the introduction of other foods amongst Canadian children
Bibliographic record
Abstract
Food-allergic children frequently avoid other foods. We hypothesized that parents of food-allergic children are not given consistent advice regarding introduction of allergenic foods; that these foods are avoided or delayed; and that there is significant anxiety when introducing new foods. An online survey was administered via Anaphylaxis Canada ’s website to Canadian parents and caregivers who are registered members of this organization and who have a child with a food allergy. 644 parents completed the online survey (60% male children, average age at diagnosis 21.8 months). The most common allergies were peanut (49%), milk (23%), and egg (18%). 51% of families were given advice regarding the introduction of other allergenic foods, 97% followed through with this advice. 72% were told to avoid certain foods, 41% to delay certain foods, and 14% were given varied advice. 58% of parents avoided or delayed other highly allergenic foods, mainly due to a fear of allergic reaction or anaphylaxis (93%). 69% of children did not have an allergic reaction when these foods were introduced. 68% of parents felt moderate or high levels of anxiety when introducing other foods. Families of children with food allergies receive varied advice regarding the introduction of new foods. The majority of children did not have an allergic reaction to the new food, even if it was initially avoided or delayed. Most parents feel moderate to high levels of anxiety when introducing new foods to their children. A more consistent approach to this advice may decrease parental anxiety.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".