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Food Allergy: From Clinical Presentation to Management and Prevention

2014· article· en· W2057829162 on OpenAlexvenueno aff
Saida Rezaković, Marta Navratil, Kristina Žužul

Bibliographic record

VenueJournal of Nutritional Therapeutics · 2014
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsnot available
Fundersnot available
KeywordsPresentation (obstetrics)Food allergyAllergyMedicineImmunologySurgery

Abstract

fetched live from OpenAlex

Food allergy is an adverse immune-mediated pathological reaction directed toward proteins or glycoproteins in food. It affects the skin, gastrointestinal, respiratory and cardiovascular systems, resulting in a broad spectrum of diverse clinical presentations. Consequently, establishing a diagnosis can present a great challenge. The prevalence rate of food allergy is increasing, particularly in modern industrialized countries, and is becoming a significant public health problem. There is still no current treatment, and avoidance of suspected food allergens remains the most important treatment modality. However, in order to avoid unnecessary dietary restrictions, food hypersensitivity should be confirmed using allergy tests prior to introduction of elimination diet. In cases of validation of food allergy, avoiding suspected foods are recommended. Education of patients is the cornerstone of prevention and therapy; providing all relevant information on how to exclude specific foods from the patient's diet, as well as how to detect and manage allergic reactions, especially in severe cases like anaphylaxis. This review aims at presenting the clinical picture and diagnosis, as well as discussing current treatment and preventive strategies for different types of food allergies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.869
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.099
GPT teacher head0.403
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations0
Published2014
Admission routes1
Has abstractyes

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