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Record W2101418369 · doi:10.1136/heart.89.5.502

What level of physical activity protects against premature cardiovascular death? The Caerphilly study

2003· article· en· W2101418369 on OpenAlexfundno aff
Shicheng Yu

Bibliographic record

VenueHeart · 2003
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
FundersMedical Research CouncilQueen's UniversityBritish Heart Foundation
KeywordsMedicinePhysical activityGerontologyPhysical therapy

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine the optimal intensity of leisure time physical activity (LTPA) to decrease the risk of all cause, cardiovascular disease (CVD), and coronary heart disease (CHD) mortality in a population sample of middle aged British men. DESIGN: Prospective study of middle aged men with an 11 year follow up. SETTING: A whole population sample of men from Caerphilly, South Wales, UK. SUBJECTS: 1975 men aged 49-64 years without historical or clinical evidence of CHD at baseline examination. MAIN OUTCOME MEASURES: All cause, CVD, and CHD mortality. RESULTS: Total (cumulative) LTPA had a graded, significant relation with all cause, CVD, and CHD mortality but no trend with cancer deaths. When different intensities of activity were considered, light and moderate intensity LTPA had inconsistent and non-significant relations with all cause, CVD, or CHD mortality whether adjusted only for age or for other cardiovascular risk factors. In contrast a significant dose-response relation was found for heavy intensity LTPA for all cause, CVD, and CHD mortality fully adjusted for other risk factors. CONCLUSIONS: These data suggest that, in a population of men without evidence of CHD at baseline, only leisure exercise classified as heavy or vigorous was independently associated with reduced risk of premature death from CVD.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.133
GPT teacher head0.348
Teacher spread0.215 · 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

Citations182
Published2003
Admission routes1
Has abstractyes

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