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Record W1968388722 · doi:10.2337/dc12-0101

Relationship of Insulin Sensitivity, Insulin Secretion, and Adiposity With Insulin Clearance in a Multiethnic Population

2012· article· en· W1968388722 on OpenAlexaff
Carlos Lorenzo, Anthony J. Hanley, Lynne E. Wagenknecht, Marian Rewers, Darko Stefanovski, Mark O. Goodarzi, Steven M. Haffner

Bibliographic record

VenueDiabetes Care · 2012
Typearticle
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsUniversity of TorontoMount Sinai Hospital
FundersNational Center for Research ResourcesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood Institute
KeywordsMedicineInsulinInsulin sensitivityInternal medicineEndocrinologyDiabetes mellitusPopulationInsulin resistanceEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: We aimed to examine insulin clearance, a compensatory mechanism to changes in insulin sensitivity, across sex, race/ethnicity populations, and varying states of glucose tolerance. RESEARCH DESIGN AND METHODS: We measured insulin sensitivity index (S(I)), acute insulin response (AIR), and metabolic clearance rate of insulin (MCRI) by the frequently sampled intravenous glucose tolerance test in 1,295 participants in the Insulin Resistance Atherosclerosis Study. RESULTS: MCRI was positively related to S(I) and negatively to AIR and adiposity across sex, race/ethnicity populations, and varying states of glucose tolerance, adiposity, and family history of diabetes. Differences in MCRI by race/ethnicity (lower in African Americans and Hispanics compared with non-Hispanic whites) and glucose tolerance were largely explained by differences in adiposity, S(I), and AIR. CONCLUSIONS: Insulin sensitivity, insulin secretion, and adiposity are correlates of insulin clearance and appear to explain differences in insulin clearance by race/ethnicity and glucose tolerance status.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.013
GPT teacher head0.238
Teacher spread0.225 · 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 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

Citations47
Published2012
Admission routes1
Has abstractyes

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