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Record W7100012838

The high rates of overweight and obesity among Canadianchildren and youth and the quality of their diet are of con-cern.1 Results from the

2016· article· en· W7100012838 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsnot available
Fundersnot available
KeywordsSnackingOverweightObesityQuality (philosophy)Health promotionHealthy eatingPublic health
DOInot available

Abstract

fetched live from OpenAlex

Canadian Community Health Survey, Cycle 2.2, Nutrition (CCHS 2.2) show that most snacks consumed by Canadians are foods not included in the four food groups of Canada’s Food Guide2 and are generally high in energy, fats and/or sugars. Improving the diet quality of children and youth is a pri-ority in Canada.1 There is growing interest in Canada for supporting physical activ-ity for children and youth in the after-school (AS) time period.3 Integrating the promotion of healthy eating into such interven-tions can help to improve the nutritional health of children and youth.4 Results of the analysis of the snacking habits of children attending elementary school in the United States raise some con-cerns regarding the quality of their snacks.5 However, in Canada, lit-tle is known about the AS snacking habits of children and adolescents.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.007
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.031
GPT teacher head0.285
Teacher spread0.253 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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