Zéro allergie research clinic: a clinical and research initiative in oral immunotherapy for managing IgE-mediated food allergy
Bibliographic record
Abstract
BACKGROUND AND METHODS: The Zéro allergie research clinic (Saguenay, Canada) is a clinical and research initiative in oral immunotherapy (OIT) for managing IgE-mediated food allergy (FA). A total of 183 children with FA and 27 non-allergic siblings were recruited to date in the Zéro allergie cohort (ZAC) to better understand biological mechanisms underlying FA and OIT prognosis. The primary aims are to (a) better understand the genetic, epigenetic, transcriptomic, metabolomic, and microbial diversity associated with FA; (b) establish the multi-omics and microbial diversity profiles of children following OIT to identify predictive prognosis biomarkers, (c) make OIT more accessible to the population of the Saguenay-Lac-Saint-Jean region, and (d) build a biobank of data and biological material. RESULTS: The ZAC constitutes a unique and rich biobank of biological samples (blood, buccal swabs, microbiota samples [intestinal, buccal, nasal, and cutaneous]) combined with clinical data and more than 75 phenotypic characteristics. CONCLUSIONS: This represents an innovative interdisciplinary initiative by researchers, allergists, and paediatricians to make FA care accessible to a greater number of children with IgE-mediated FA. Ultimately, it will contribute to provide more accessible treatment options with greater chances of success through a better understanding of the biological nature of FA and OIT.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".