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Record W4200257793 · doi:10.1093/geroni/igab046.1481

Cardiovascular Risk Factors and Carotid Intima Media Thickness: Mediation and Interaction by Grip Strength

2021· article· en· W4200257793 on OpenAlexaffabout
Christian W Mendo, Mark R. Keezer, Marie‐Pierre Sylvestre

Bibliographic record

VenueInnovation in Aging · 2021
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsMcGill UniversityUniversité de Montréal
Fundersnot available
KeywordsGrip strengthMediationVulnerability (computing)Intima-media thicknessMedicineStressorDiseaseInternal medicineCardiologyPhysical therapyCarotid arteriesClinical psychologyComputer science

Abstract

fetched live from OpenAlex

Abstract Frailty is often described as being an increased vulnerability to the effects of stressors. There is little research investing how frailty may act as either a mediator or participate in interactions in the associations between risk factors and chronic disease. We will present novel analyses of the Canadian Longitudinal Study on Aging, focusing on the 30,000 study participants who underwent serial physical evaluations at one of 11 data collection sites between 2011 and 2018. Using the 4- way decomposition method elaborated by Vanderweele, we investigate the role of grip strength, as a component of physical frailty, in the effect of cardiovascular risk factors on the atherosclerotic burden of individuals (measured using carotid intima media thickness). Our findings clarify the mechanisms underlying of grip strength in the associations between cardiovascular risk factors and carotid intima media thickness.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.092
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.266
Teacher spread0.250 · 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 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

Citations0
Published2021
Admission routes2
Has abstractyes

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