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Record W4404871902 · doi:10.1186/s13223-024-00937-0

Canadian Society of Allergy and Clinical Immunology position statement: panel testing for food allergies

2024· review· en· W4404871902 on OpenAlexaffvenueabout
Abdulrahman Al Ghamdi, Elissa M. Abrams, Stuart Carr, Mariam Hanna, Sari M. Herman, Elana Lavine, Harold Kim, Timothy K. Vander Leek, Douglas P. Mack

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2024
Typereview
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsUniversity of AlbertaWestern UniversityUniversity of ManitobaMcMaster UniversityHumber River Regional HospitalStollery Children's HospitalUniversity of British ColumbiaUniversity of Toronto
Fundersnot available
KeywordsFood allergyMedicineAllergyPosition statementTest (biology)PsychosocialPosition paperEnvironmental healthFamily medicineImmunologyPsychiatryPathology

Abstract

fetched live from OpenAlex

This position statement addresses the critical concerns and recommended practices surrounding the use of panel food testing for diagnosing food allergies. Food allergies are a significant public health concern, and the misdiagnosis of food allergies remains a prevalent concern, made worse by the ongoing use of panel food testing. The practice of screening patients for multiple food allergens, regardless of clinical relevance, is commonly referred to as "panel food testing." Fundamentally, a panel food test is not simply a single test; a panel food test is a series of several distinct tests for multiple foods, each with its own variable predictive value. These tests have not been adequately validated as screening tests and carry a considerable false positive rate. The resulting false diagnoses lead to unnecessary dietary restrictions, increased healthcare costs, and significant psychosocial distress for patients and their families.

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)0.009
metaresearch head score (Gemma)0.012
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.005
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0040.002
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0100.008

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 head0.123
GPT teacher head0.415
Teacher spread0.292 · 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

Citations0
Published2024
Admission routes3
Has abstractyes

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