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Record W2107859942 · doi:10.1097/wox.0b013e3181defeb9

World Allergy Organization (WAO) Diagnosis and Rationale for Action against Cow's Milk Allergy (DRACMA) Guidelines

2010· article· en· W2107859942 on OpenAlexfundno aff
Alessandro Fiocchi, Jan Brożek, Holger J. Schünemann, Sami L. Bahna, Andrea von Berg, Kirsten Beyer, Martín Bózzola, Julia E. Bradsher, Enrico Compalati, Motohiro Ebisawa, María Antonieta Guzmán, Haiqi Li, Ralf G. Heine, Paul K. Keith, Gideon Lack, Massimo Landi, Alberto Martelli, F. Rancé, Hugh A. Sampson, Aírton Tetelbom Stein, Luigi Terracciano, Stefan Vieths

Bibliographic record

VenueWorld Allergy Organization Journal · 2010
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsnot available
FundersMcMaster UniversityDanone
KeywordsMedicineBiostatisticsFamily medicineEpidemiologyPediatricsEmergency departmentClinical immunologyAllergyInternal medicineImmunology

Abstract

fetched live from OpenAlex

T here are no surveys of population and geographical trends in food allergy in adults or children (though the situation is different in pediatric asthma and rhinitis) and this unmet need is particularly felt for CMA. The perception of milk allergy is far more frequent than confirmed CMA. Patient reports of CMA range between 1 and 17.5%, 1 and 13.5%, and 1 to 4% in preschoolers, at children 5 to 16 years of age and adults respectively. Cow's milk-specific IgE sensitization point prevalence progressively decreased from about 4% at 2 years to less than 1% at 10 years of age in the German Multi-Centre Allergy Study. The most reliable data in epidemiology are those from birth cohorts that are free from selection bias. There are 5 such challenge-confirmed studies. The CMA prevalence during infancy ranged from 1.9% in a Finnish study, 2.16% in the Isle of Wight, 2.22% in a study from Denmark, 2.24% in the Netherlands, and up to 4.9% in Norway.

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)0.006
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0110.009

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 head0.044
GPT teacher head0.321
Teacher spread0.277 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations637
Published2010
Admission routes1
Has abstractyes

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