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Record W1986128461 · doi:10.1155/2011/360257

Physical Activity Plays an Important Role in Body Weight Regulation

2010· article· en· W1986128461 on OpenAlexafffund
Jean‐Philippe Chaput, Lars Klingenberg, Mads Rosenkilde, Jo‐Anne Gilbert, Angelo Tremblay, Anders Sjödin

Bibliographic record

VenueJournal of Obesity · 2010
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversité Laval
FundersInstituto DanoneDanoneKøbenhavns UniversitetCanada Research ChairsDanone Institute of CanadaNordea-fonden
KeywordsMedicineOvereatingWeight lossEnergy expenditurePhysical activityWeight gainObesityPhysical therapySedentary lifestyleGerontologyPhysical medicine and rehabilitationBody weightEndocrinology

Abstract

fetched live from OpenAlex

Emerging literature highlights the need to incorporate physical activity into every strategy intended to prevent weight gain as well as to maintain weight loss over time. Furthermore, physical activity should be part of any plan to lose weight. The stimulus of exercise provides valuable metabolic adaptations that improve energy and macronutrient balance regulation. A tight coupling between energy intake and energy expenditure has been documented at high levels of physical exercise, suggesting that exercise may improve appetite control. The regular practice of physical activity has also been reported to reduce the risk of stress-induced weight gain. A more personalized approach is recommended when planning exercise programs in a clinical weight loss setting in order to limit the compensatory changes associated to exercise-induced weight loss. With modern environment promoting overeating and sedentary behavior, there is an urgent need for a concerted action including legislative measures to promote healthy active living in order to curb the current epidemic of chronic diseases.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0020.000
Open science0.0000.001
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 head0.009
GPT teacher head0.278
Teacher spread0.269 · 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

Citations165
Published2010
Admission routes2
Has abstractyes

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