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Record W2001144558 · doi:10.1016/j.pmedr.2014.11.003

Added sugars in kids' meals from chain restaurants

2014· article· en· W2001144558 on OpenAlexafffundabout
Mary J. Scourboutakos, Zhila Semnani‐Azad, Mary R. L’Abbé

Bibliographic record

VenuePreventive Medicine Reports · 2014
Typearticle
Languageen
FieldMedicine
TopicDiet, Metabolism, and Disease
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchUniversity of TorontoCanadian Stroke NetworkCancer Care Ontario
KeywordsSugarAdded sugarCalorieFree sugarFood scienceMedicineBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To analyze the added sugars in kids' meals from Canadian chain restaurants in relation to the World Health Organization's proposed sugar recommendation (less than 5% of total daily calories should come from added sugars) and current recommendation (less than 10% of total daily calories should come from added sugars). METHODS: Total sugar levels were retrieved from the websites of 10 fast-food and 7 sit-down restaurants in 2010. The added sugar levels in 3178 kids' meals from Canadian chain restaurants were calculated in 2014 (in Toronto, Canada) by subtracting all naturally occurring sugars from the total sugar level. RESULTS: The average amount of added sugars in restaurant kids' meals (25 ± 0.36 g) exceeded the WHO's proposed daily recommendation for sugar intake. There was a wide range of added sugar levels in kids' meals ranging from 0 g to 114 g. 50% of meals exceeded the WHO's proposed daily sugar recommendation, and 19% exceeded the WHO's current daily sugar recommendation. CONCLUSION: There is a wide range of sugar levels in kids' meals from restaurants, and many contain more than a day's worth of sugar.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.014
GPT teacher head0.293
Teacher spread0.279 · 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 designObservational
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

Citations23
Published2014
Admission routes3
Has abstractyes

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