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Record W2114745543 · doi:10.1017/s1368980009990309

The growing Canadian energy gap: more the can than the couch?

2009· article· en· W2114745543 on OpenAlexafffundabout
Joyce Slater, Christopher G. Green, Gustaaf P. Sevenhuysen, Barry Edginton, John O’Neil, M. A. Heasman

Bibliographic record

VenuePublic Health Nutrition · 2009
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsSimon Fraser UniversityUniversity of WinnipegManitoba HealthUniversity of Manitoba
FundersCanadian Institutes of Health ResearchUniversity of ManitobaManitoba Health Research Council
KeywordsPer capitaEnergy balancePopulationEnergy consumptionEnergy (signal processing)ObesityDemographyEnvironmental healthMedicineBiologyMathematicsStatisticsEcology

Abstract

fetched live from OpenAlex

OBJECTIVE: The present study describes the trajectory of the energy gap (energy imbalance) in the Canadian population from 1976 to 2003, its temporal relationship to adult obesity, and estimates the relative contribution of energy availability and expenditure to the energy gap. It also assesses which foods contributed the most to changes in available energy over the study period. DESIGN: Annual estimates of the energy gap were derived by subtracting population-adjusted per capita daily estimated energy requirements (derived from Dietary Reference Intakes) from per capita daily estimated energy available (obtained from food balance sheets). Food balance sheets were used to assess which foods contributed to changes in energy availability. Adult obesity rates were derived from six national surveys. The relationship to the energy gap was assessed through regression analysis. RESULTS: Between 1976 and 2003, per capita daily estimated energy availability increased by 18 % (1744 kJ), and increased energy availability was the major driver of the increased energy gap. Salad oils, wheat flour, soft drinks and shortening accounted for the majority of the net increase in energy availability. Adult obesity was significantly correlated with the energy gap over the study period. CONCLUSIONS: The widening energy gap is being driven primarily by increased energy availability. The food commodities driving the widening energy gap are major ingredients in many energy-dense convenience foods, which are being consumed with increasing frequency in Canada. Policies to address population obesity must have a strong nutritional focus with the objective of decreasing energy consumption at the population level.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.798
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.293
Teacher spread0.261 · 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.

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

Citations28
Published2009
Admission routes3
Has abstractyes

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