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Record W2013803139 · doi:10.3148/69.3.2008.147

<i>Gluten-Free and Regular Foods:</i> A Cost Comparison

2008· article· en· W2013803139 on OpenAlexaffvenue
L. F. Stevens, Mohsin Rashid

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2008
Typearticle
Languageen
FieldMedicine
TopicCeliac Disease Research and Management
Canadian institutionsDalhousie University
Fundersnot available
KeywordsGluten freeGlutenFood scienceProduct (mathematics)Unit priceMedicineMathematicsChemistryEconomics

Abstract

fetched live from OpenAlex

PURPOSE: The treatment of celiac disease is a strict gluten-free diet for life. This diet is assumed to be more expensive, although no studies confirm this assumption. In the current study, the prices of gluten-free foods and regular (gluten-containing) foods were compared to determine if and to what extent gluten-free products are more expensive. METHODS: Prices were compared for all food products labelled "gluten-free" and comparable gluten-containing food items in the same group available at two large-chain general grocery stores. The unit cost of each food, calculated as the price in dollars per 100 grams of each product, was calculated for purposes of comparison. RESULTS: All 56 gluten-free products were more expensive than regular products. The mean (+/- standard deviation) unit price for gluten-free products was $1.71 (+/- 0.93) compared with $0.61 (+/- 0.38) for regular products (p<0.0001). On average, gluten-free products were 242% more expensive than regular products (+/- 212; range, 5% to 1,000%). CONCLUSIONS: All the commercially available products labelled gluten-free were significantly more expensive than comparable products. This information will be useful to dietitians who counsel individuals and families with celiac disease, and to celiac advocacy groups for lobbying the government about financial compensation.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.621

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.120
GPT teacher head0.411
Teacher spread0.291 · 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 designNot applicable
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

Citations138
Published2008
Admission routes2
Has abstractyes

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