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Record W4405913031 · doi:10.1186/s13223-024-00930-7

Immunoglobulin E (IgE)-mediated food allergy

2024· review· en· W4405913031 on OpenAlexaffvenue
Philippe Bégin, Susan Waserman, Jennifer L. P. Protudjer, Samira Jeimy, Wade Watson

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2024
Typereview
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsDalhousie UniversityWestern UniversityIzaak Walton Killam Health CentreUniversity of ManitobaChildren's Hospital Research Institute of ManitobaMcMaster UniversityUniversité de Montréal
FundersSanofiAstraZeneca
KeywordsImmunoglobulin EFood allergyImmunologyAllergyFood proteinAntibodyBiologyFood science

Abstract

fetched live from OpenAlex

Food allergy is defined as an adverse immunologic response to a food. Immunoglobulin E (IgE)-mediated reactions to foods are associated with a broad range of signs and symptoms that may involve any of the following body systems: the skin, gastrointestinal tract, respiratory tract, and cardiovascular system. IgE-mediated food allergy is a leading cause of anaphylaxis. Therefore, timely and appropriate diagnosis and treatment are imperative. A diagnosis of food allergy entails a careful history and diagnostic tests, which may include skin prick tests, serum-specific IgE, and oral food challenge. The goal of food allergy care is to empower patients and caregivers to manage the risk of food-allergic reactions, reduce food allergy-related anxiety, and achieve a sense of control over their condition. This can be achieved in different ways for different patients and across different life stages. This article provides an overview of the epidemiology, pathophysiology, diagnosis, and management of IgE-mediated food allergy.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.003

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 head0.069
GPT teacher head0.401
Teacher spread0.332 · 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
GenreReview

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

Citations12
Published2024
Admission routes2
Has abstractyes

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