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Record W2808731012 · doi:10.2147/jaa.s162456

Food allergy and anaphylaxis

2018· review· en· W2808731012 on OpenAlexaff
David T. Yue, A Ciccolini, Ernie Avilla, Susan Waserman

Bibliographic record

VenueJournal of Asthma and Allergy · 2018
Typereview
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsMcMaster UniversityHealth Sciences Centre
FundersAimmune Therapeutics
KeywordsAnaphylaxisMedicineDesensitization (medicine)Food allergyAllergyAllergenImmunologyIntensive care medicineDermatologyInternal medicine

Abstract

fetched live from OpenAlex

Anaphylaxis is a severe and potentially life-threatening allergic reaction. There are numerous potential causes, with food allergy being the leading cause in children and the focus of this review. Most reactions involve an IgE-mediated mechanism, although non-IgE-mediated and nonimmunologic reactions can occur. Various cofactors to be discussed can place certain individuals at an increased risk of severe or fatal anaphylaxis. The clinical manifestations of anaphylaxis are broad and may involve multiple body systems. Diagnosis of food-related anaphylaxis is primarily based on signs and symptoms and supported, wherever possible, by identification and confirmation of a culprit food allergen. First-line treatment of anaphylaxis is intramuscular administration of epinephrine. Long-term management is generally focused on strict allergen avoidance and more recently on food desensitization using immunotherapy. This review provides an overview of anaphylaxis with a specific focus on 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.331
Teacher spread0.290 · 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 teacher head, not a consensus.

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

Citations53
Published2018
Admission routes1
Has abstractyes

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