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Record W2035202711 · doi:10.4103/1947-2714.136901

The "Fit but Fat" paradigm addressed using accelerometer-determined physical activity data

2014· article· en· W2035202711 on OpenAlexaff
Paul D. Loprinzi, Ellen Smit, Hyo Lee, Carlos J. Crespo, Ross E. Andersen, S. N. Blair

Bibliographic record

VenueNorth American Journal of Medical Sciences · 2014
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineAccelerometerPhysical activityPhysical medicine and rehabilitationData scienceComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: No studies have addressed the "fit but fat" paradigm using accelerometry data. AIM: The study was to determine if 1) higher levels of accelerometer-determined physical activity are favorably associated with biomarkers in overweight or obese persons (objective 1); and 2) overweight or obese individuals who are sufficiently active have better or similar biomarker levels than normal weight persons who are not sufficiently active (objective 2). MATERIALS AND METHODS: Data from the 2003-2006 National Health and Nutrition Examination Survey were analyzed and included 5,146 participants aged 20-85 years. RESULTS: Regarding objective 1, obese active individuals had more favorable waist circumference, C-reactive protein, white blood cells, and neutrophil levels when compared to obese inactive individuals; similar results were found for overweight adults. Regarding objective 2, there were no significant differences between normal weight inactive individuals and overweight active individuals for nearly all biomarkers. Similarly, there were no significant differences between normal weight inactive individuals and obese active individuals for white blood cells, neutrophils, low-density lipoprotein cholesterol, total cholesterol, triglycerides, glucose, or homocysteine. CONCLUSIONS: Physical activity has a protective effect on biomarkers in normal, overweight, and obese individuals, and overweight (not obese) active individuals have a similar cardiovascular profile than normal weight inactive individuals.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.985
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.244
GPT teacher head0.430
Teacher spread0.186 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations34
Published2014
Admission routes1
Has abstractyes

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