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Record W7032968009

Physical Activity Levels & Correlates 2-6 Years Post-rehabilitation in Cardiac Patients

2011· dissertation· en· W7032968009 on OpenAlexaboutno aff

Bibliographic record

VenueTSpace (University of Toronto) · 2011
Typedissertation
Languageen
FieldComputer Science
TopicEducational Robotics and Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical activityMarital statusMultivariate analysisQuality of life (healthcare)RehabilitationLife stylePhysical activity levelSocial support
DOInot available

Abstract

fetched live from OpenAlex

Many patients do not maintain physical activity (PA) post cardiac rehabilitation (CR),however few studies examine a large enough sample over the long-term. Thus, a retrospective cross-sectional study was carried out to examine PA and its correlates 2-6 years post CR; 584 graduates completed a mailed survey (mean+SD age: 69.8+9.8 years, BMI: 27+5.0 kg/m2, 80% male, 41.4+11.6 months since graduation, 36% response rate). PA was assessed using the Physical Activity Scale for the Elderly (PASE, mean+SD: 122.3+75.9). Seventy five percent of participants met Canadian PA guidelines. Greater PA was significantly associated with male sex, younger age, fear of falling, cholesterol control, self-controlled transportation, marital status, full-time work, rural location, higher VO2max, more comorbid conditions, greater perceived \nhealth, PA enjoyment, quality of life (QOL), social support, income, and CR staff support. Age,PA enjoyment, QOL, work status, cholesterol control and CR staff were significant in a multivariate model (R2=0.22, F=18.7, p<0.001).

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)0.003
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.238
Teacher spread0.226 · 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
Published2011
Admission routes1
Has abstractyes

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