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Record W2178397625 · doi:10.1093/pch/18.10.545

Dietary exposures and allergy prevention in high-risk infants

2013· article· en· W2178397625 on OpenAlexaboutno aff
Edmond S. Chan, Carl Cummings

Bibliographic record

VenuePaediatrics & Child Health · 2013
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreastfeedingFood allergyEnvironmental healthAllergyPregnancyPediatricsDiseaseBreast feedingIntensive care medicineImmunology

Abstract

fetched live from OpenAlex

Allergic conditions in children are a prevalent health concern in Canada. The burden of disease and the societal costs of proper diagnosis and management are considerable, making the primary prevention of allergic conditions a desirable health care objective. This position statement reviews current evidence on dietary exposures and allergy prevention in infants at high risk for developing allergic conditions. It revisits previous dietary recommendations for pregnancy, breastfeeding and formula feeding, and provides an approach for introducing solid foods to high-risk infants. While there is no evidence that delaying the introduction of any specific food beyond six months of age helps to prevent allergy, the protective effect of early introduction of potentially allergenic foods (at four to six months of age) remains under investigation. Recent research appears to suggest that regularly ingesting a new, potentially allergenic food may be as important as when that food is first introduced.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.064
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.016
GPT teacher head0.292
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations62
Published2013
Admission routes1
Has abstractyes

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