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Record W2025672316 · doi:10.1016/j.jaci.2013.03.043

Filaggrin gene mutation associations with peanut allergy persist despite variations in peanut allergy diagnostic criteria or asthma status

2013· letter· en· W2025672316 on OpenAlexafffundabout
Yuka Asai, Celia M.T. Greenwood, Peter Hull, Reza Alizadehfar, Moshe Ben‐Shoshan, Sara Brown, Linda Campbell, Déborah Michel, Johanne Bussières, François Rousseau, Takuya Fujiwara, Kenneth Morgan, Alan D. Irvine, W.H. Irwin McLean, Ann E. Clarke

Bibliographic record

VenueJournal of Allergy and Clinical Immunology · 2013
Typeletter
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsUniversité LavalMcGill University Health CentreUniversity of SaskatchewanJewish General HospitalMcGill University
FundersCanadian Institutes of Health ResearchWellcome Trust
KeywordsFilaggrinPeanut allergyAtopic dermatitisAllergyMedicineAsthmaOdds ratioGeneticsImmunologyFood allergyBiologyInternal medicine

Abstract

fetched live from OpenAlex

Recently, our research team found a strong and significant association between loss-of-function (LOF) mutations in filaggrin (FLG), a gene that encodes a skin barrier protein, in European and Canadian individuals with peanut allergy (PA).1 These mutations result in a barrier defect and have been associated with atopic dermatitis, asthma, and allergic rhinitis.2 This finding represents the strongest genetic risk factor found to date for PA, a highly heritable disease,3 with an estimated odds ratio (OR) between 1.9 (Canadian) and 5.3 (English, Dutch, and Irish combined).

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.037
GPT teacher head0.341
Teacher spread0.304 · 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

Citations57
Published2013
Admission routes3
Has abstractyes

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