MétaCan
Menu
Back to cohort
Record W2163131341 · doi:10.1038/oby.2008.202

Obesity‐related Changes in High‐density Lipoprotein Metabolism

2008· review· en· W2163131341 on OpenAlexaff
Arshag D. Mooradian, Michael J. Haas, Kent R. Wehmeier, Norman C.W. Wong

Bibliographic record

VenueObesity · 2008
Typereview
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineInternal medicineDyslipidemiaOverweightObesityEndocrinologyInsulin resistanceHyperlipidemiaMyocardial infarctionRisk factorCholesterolLipoproteinHigh-density lipoproteinDiabetes mellitus

Abstract

fetched live from OpenAlex

Obesity is associated with a 3-or-more-fold increase in the risk of fatal and nonfatal myocardial infarction (1,2,3,4,5,6). The American Heart Association has reclassified obesity as a major, modifiable risk factor for coronary heart disease (7). The increased prevalence of premature coronary heart disease in obesity is attributed to multiple factors (8,9,10). A principal contributor to this serious morbidity is the alterations in plasma lipid and lipoprotein levels. The dyslipidemia of obesity is commonly manifested as high plasma triglyceride levels, low high-density lipoprotein cholesterol (HDLc), and normal low-density lipoprotein cholesterol (LDLc) with preponderance of small dense LDL particles (7,8,9,10). However, there is a considerable heterogeneity of plasma lipid profile in overweight and obese people. The precise cause of this heterogeneity is not entirely clear but has been partly attributed to the degree of visceral adiposity and insulin resistance. The emergence of glucose intolerance or a genetic predisposition to familial combined hyperlipidemia will further modify the plasma lipid phenotype in obese people (11,12,13,14,15).

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.021
GPT teacher head0.266
Teacher spread0.245 · 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.

Study designOther design
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

Citations117
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueObesitySame topicDiabetes, Cardiovascular Risks, and LipoproteinsFrench-language works237,207