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Record W4406165864 · doi:10.1111/cea.14622

A Scoping Review of Cost Questionnaires Aimed at Measuring the Household Financial Burden of Food Allergy

2025· review· en· W4406165864 on OpenAlexafffund
Zoe Harbottle, Michael A. Golding, Ayel Luis R. Batac, Andrew Fong, Mê‐Linh Lê, Elissa M. Abrams, Edmond S. Chan, Moshe Ben‐Shoshan, Peter Hsu, Jodi Shroba, Juho E. Kivistö, Matthew Greenhawt, Gregory Mason, Mika J. Mäkelä, Antonella Muraro, S. Ahlstedt, Jennifer L. P. Protudjer

Bibliographic record

VenueClinical & Experimental Allergy · 2025
Typereview
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsMcGill UniversityMcGill University Health CentreUniversity of ManitobaMontreal Children's HospitalGeorge & Fay Yee Centre for Healthcare InnovationBC Children's HospitalUniversity of British ColumbiaChildren's Hospital Research Institute of Manitoba
FundersUniversity of Manitoba
KeywordsGrey literatureMedicineSystematic reviewHealth careMEDLINEMedical educationFamily medicineEnvironmental healthPolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

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)0.021
metaresearch head score (Gemma)0.073
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.073
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.008
Bibliometrics0.0190.020
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.170
GPT teacher head0.456
Teacher spread0.285 · 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 designSystematic review
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

Citations1
Published2025
Admission routes2
Has abstractyes

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