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Obesity

2014· book-chapter· en· W4256449063 on OpenAlexaboutno aff
John Wass, Katharine R. Owen, Helen Turner

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicPharmacology and Obesity Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsWaistMedicineObesityBody mass indexSarcopenic obesityClassification of obesityCircumferenceInternal medicineAbdominal obesityWaist-to-height ratioBody volume indexBody fat distributionAdipose tissueEndocrinologyFat massMathematics

Abstract

fetched live from OpenAlex

Obesity is defined as an excess of body fat sufficient to adversely affect health. Body mass index (BMI) and waist circumference, as a measure of fat distribution, are the most commonly used measures, but a clinical staging system is increasingly used to determine risk and management (see Box 15.1). BMI is an imprecise measure of adiposity and does not account for fat distribution, which may better determine metabolic and cardiovascular risk at lower BMI. Lower cut-off values for BMI and waist circumference are applicable to non-Caucasian ethnic groups: cut-off points for increased risk varies from 22kg/m2 to 25kg/m2 in different Asian populations, and for high risk from 26kg/m2 to 31kg/m2. Central obesity may reflect increased visceral (intra-abdominal fat) stores and/or ‘ectopic’ fat (fat stored in liver, muscle, pancreas, and epicardium) more directly linked to pathophysiology, such as insulin...

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.291
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.2910.201

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 head0.022
GPT teacher head0.281
Teacher spread0.258 · 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
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

Citations0
Published2014
Admission routes1
Has abstractyes

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