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Record W2489118219 · doi:10.3148/cjdpr-2016-012

Nutrient and Food Group Intakes of Manitoba Children and Youth: A Population-Based Analysis by Pulse and Soy Consumption Status

2016· article· en· W2489118219 on OpenAlexaffvenueabout
Adriana N. Mudryj, Harold M. Aukema, Paul Fieldhouse, Bo Nancy Yu

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2016
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsManitoba HealthUniversity of Manitoba
Fundersnot available
KeywordsEnvironmental healthConsumption (sociology)MedicineFood groupPopulationHealthy eatingFood scienceGerontologyPhysical activityPhysical therapyBiology

Abstract

fetched live from OpenAlex

Poor eating habits among children are associated with negative health outcomes. The objective of this study was to use pulse/soy consumption as an indicator to evaluate the eating profile of young Manitobans. Data from the Canadian Community Health Survey Cycle 2.2 were used for analysis and restricted to Manitoba residents aged 2 to 18 years (n = 1840). Consumers were identified as individuals who reported eating at least 1 pulse/soy product during their recall. On any given day, 8.2% of Manitobans reported consumption of pulses/soy. Intakes of fibre, protein, magnesium, and zinc were higher in consumers only when expressed relative to total caloric intake. Consumers also reported increased intakes of meat and alternatives. Total intakes of vitamin D, fibre, and fruit and vegetable consumption were low among all groups. Sodium intakes in both groups were high when compared with levels recommended by health professionals. These results indicate that there are many dietary issues affecting Manitoba children, suggesting the need for more research targeting dietary habits of children and youth, the quality of the food supply, and effective strategies in nutrition education.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.317
Threshold uncertainty score0.638

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.049
GPT teacher head0.332
Teacher spread0.283 · 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 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

Citations15
Published2016
Admission routes3
Has abstractyes

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