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Record W2003646409 · doi:10.3109/09637486.2015.1035232

Traditional food consumption is associated with better diet quality and adequacy among Inuit adults in Nunavut, Canada

2015· article· en· W2003646409 on OpenAlexaffabout
Tony Sheehy, Fariba Kolahdooz, Cindy Roache, Sangita Sharma

Bibliographic record

VenueInternational Journal of Food Sciences and Nutrition · 2015
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Alberta
FundersAmerican Diabetes Association
KeywordsEnvironmental healthFood frequency questionnaireConsumption (sociology)NutrientFood groupPopulationGeographyHealthy eatingMedicineDemographyFood scienceGerontologyPhysical activityBiologyEcology

Abstract

fetched live from OpenAlex

The Inuit population is undergoing a rapid nutrition transition as a result of reduced consumption of traditional foods. This study aims to describe the differences in dietary adequacy between non-traditional and traditional eaters among Inuit populations in Nunavut, Canada. A cross-sectional survey was conducted using a culturally appropriate quantitative food frequency questionnaire. Participants included 208 Inuit adults from three isolated communities in Nunavut. Traditional eaters consumed a more nutrient-dense diet and achieved better dietary adequacy than non-traditional eaters. Traditional foods accounted for 7 and 27% of energy intake among non-traditional and traditional eaters, respectively. Non-nutrient-dense foods accounted for a greater proportion of energy intake in non-traditional eaters; however, these were consumed in significant amounts by both the groups (36 and 27% of total energy). Consumption of traditional foods is associated with greater diet quality and dietary adequacy. Efforts should be made to promote traditional and non-traditional foods of high-nutritional quality.

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 score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
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 head0.117
GPT teacher head0.366
Teacher spread0.249 · 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

Citations28
Published2015
Admission routes2
Has abstractyes

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