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Record W4394738544 · doi:10.1016/j.anai.2024.02.012

Early solid introduction to prevent IgE–mediated food allergy should continue unabated while we learn more about food protein–induced enterocolitis syndrome prevalence

2024· article· en· W4394738544 on OpenAlexaff
Linlei Ye, Stephanie C. Erdle, Elissa M. Abrams, Edmond S. Chan

Bibliographic record

VenueAnnals of Allergy Asthma & Immunology · 2024
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsUniversity of ManitobaBC Children's HospitalUniversity of British ColumbiaUniversity of Alberta
Fundersnot available
KeywordsMedicineFood allergyEnterocolitisFood proteinAllergyFood hypersensitivityImmunoglobulin EOral food challengeImmunologyIntensive care medicineFood scienceInternal medicineAntibody

Abstract

fetched live from OpenAlex

Food protein–induced enterocolitis syndrome (FPIES) is a non–IgE-mediated allergy that typically presents in infancy with the introduction of infant formula or solid foods. Whereas previously thought to be rare, recent studies have reported a notable increase in prevalence, particularly among peanut and egg (Table 1). Moreover, FPIES to peanut has historically been uncommon. Interestingly, several case series have described the increased incidence of peanut FPIES in recent years and cited the 2015 Learning Early about Peanut Allergy study as a potential driving factor.

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)0.004
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.034
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0340.011

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 head0.041
GPT teacher head0.319
Teacher spread0.278 · 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
GenreCommentary

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

Citations3
Published2024
Admission routes1
Has abstractyes

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