Practical tips for the use of the Canadian milk ladder for paediatricians
Bibliographic record
Abstract
Cow’s milk allergy is a common cause of anaphylaxis in children although most milk-allergic children can ingest extensively baked milk (BM) without an allergic reaction (1,2). BM ingestion in these children can accelerate milk tolerance (1,2). Milk ladders are home-based tools to support parents with introducing milk products into a milk-allergic child’s diet (3). This approach carries a risk of allergic reactions and needs informed consent. In parallel to the milk ladder, public health efforts should be made to prevent milk allergies through education about the importance of early and sustained exposure to cow’s milk formula (4–6). Heating milk causes conformational changes in milk protein altering its ability to induce allergic reactions (1). Approximately 75% of children who are allergic to liquid, pasteurized milk are non-reactive to milk which has been baked into wheat-based muffin (1). To discover if a child can tolerate BM, allergists can offer a medically-supervised BM oral food challenge (OFC). The child would eat a BM muffin over a few hours. The OFC reveals the child to be allergic or not allergic that very day. Children who tolerate BM muffins will likely outgrow their milk allergy and are encouraged to routinely eat BM (1). Children who are BM reactive may have a severe allergic reaction (1,5).
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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 | 0.008 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.110 | 0.047 |
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".