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Obesity: a disease or a biological adaptation? An update

2012· review· en· W2166558149 on OpenAlexafffund
Jean‐Philippe Chaput, Éric Doucet, Angelo Tremblay

Bibliographic record

VenueObesity Reviews · 2012
Typereview
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversité LavalUniversity of OttawaChildren's Hospital of Eastern Ontario
FundersCanadian Institutes of Health Research
KeywordsObesityWeight gainAppetiteLeptinMedicineDiseasePopulationWeight lossEnvironmental healthPsychologyEndocrinologyGerontologyInternal medicineBody weight

Abstract

fetched live from OpenAlex

Obesity is characterized by the accumulation of excess body fat and can be conceptualized as the physical manifestation of chronic energy excess. An important challenge of today's world is that our so-called obesogenic environment is conducive to the consumption of energy and unfavourable to the expenditure of energy. The modern, computer-dependent, sleep-deprived, physically inactive humans live chronically stressed in a society of food abundance. From a physiological standpoint, the excess weight gain observed in prone individuals is perceived as a normal consequence to a changed environment rather than a pathological process. In other words, weight gain is a sign of our contemporary way of living or a 'collateral damage' in the physiological struggle against modernity. Additionally, substantial body fat loss can complicate appetite control, decrease energy expenditure to a greater extent than predicted, increase the proneness to hypoglycaemia and its related risk towards depressive symptoms, increase the plasma and tissue levels of persistent organic pollutants that promote hormone disruption and metabolic complications, all of which are adaptations that can increase the risk of weight regain. In contrast, body fat gain generally provides the opposite adaptations, emphasizing that obesity may realistically be perceived as an a priori biological adaptation for most individuals. Accordingly, prevention and treatment strategies for obesity should ideally target the main drivers or root causes of body fat gain in order to be able to improve the health of the population.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.004

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 head0.274
GPT teacher head0.406
Teacher spread0.132 · 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; both teacher heads agree on what is shown here.

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

Citations88
Published2012
Admission routes2
Has abstractyes

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