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Record W2037451537 · doi:10.1016/j.pcad.2013.09.010

Cardiac Rehabilitation Series: Canada

2013· article· en· W2037451537 on OpenAlexafffundabout
Sherry L. Grace, Stephanie Bennett, Chris I. Ardern, Alexander M. Clark

Bibliographic record

VenueProgress in Cardiovascular Diseases · 2013
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity of AlbertaYork UniversityUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsMedicineRehabilitationSeries (stratigraphy)Physical medicine and rehabilitationPhysical therapy

Abstract

fetched live from OpenAlex

Cardiovascular disease is among the leading causes of mortality and morbidity in Canada. Cardiac rehabilitation (CR) has a long robust history here, and there are established clinical practice guidelines. While the effectiveness of CR in the Canadian context is clear, only 34% of eligible patients participate, and strategies to increase access for under-represented groups (e.g., women, ethnic minority groups) are not yet universally applied. Identified CR barriers include lack of referral and physician recommendation, travel and distance, and low perceived need. Indeed there is now a national policy position recommending systematic inpatient referral to CR in Canada. Recent development of 30 CR quality indicators and the burgeoning national CR registry will enable further measurement and improvement of the quality of CR care in Canada. Finally, the Canadian Association of CR is one of the founding members of the International Council of Cardiovascular Prevention and Rehabilitation, to promote CR globally.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score0.481

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.1440.027

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 head0.006
GPT teacher head0.265
Teacher spread0.258 · 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 designNot applicable
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

Citations87
Published2013
Admission routes3
Has abstractno

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