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Record W2058434082 · doi:10.1139/h00-001

Obesity Reduction Through Lifestyle Modification

2000· review· en· W2058434082 on OpenAlexaffabout
Robert Ross, Ian Janssen, Angelo Tremblay

Bibliographic record

VenueCanadian Journal of Applied Physiology · 2000
Typereview
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsObesityMedicineWeight lossOverweightLifestyle modificationAbdominal obesityType 2 diabetesDiseaseIntervention (counseling)Physical therapyPublic healthDiabetes mellitusGerontologyMetabolic syndromeEnvironmental healthInternal medicineEndocrinologyPsychiatry

Abstract

fetched live from OpenAlex

Obesity is a worldwide public health problem. One in three Canadians is overweight, a prevalence that is already high and increasing. Moreover, 54% of men and 37% of Canadian women are characterized as abdominally obese, the phenotype that is strongly associated with cardiovascular disease and type II diabetes. These observations underscore the importance of considering the efficacy of methods commonly used to reduce total and abdominal obesity. These strategies include a decrease in energy intake (diet), an increase in energy expenditure (exercise), or pharmacological intervention. The combination of diet and exercise is more commonly prescribed, with pharmacological intervention suggested only when lifestyle changes fail to achieve weight loss. The aim of this report is to review current knowledge regarding the influence of diet and exercise as treatment strategies for obesity reduction and provide recommendations for attaining and maintaining a healthy weight. The importance of diet composition in the treatment of obesity is also considered.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.052
GPT teacher head0.316
Teacher spread0.264 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations25
Published2000
Admission routes2
Has abstractyes

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