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Record W2400786048

Cardiac rehabilitation and secondary prevention services in Ontario: recommendations from a consensus panel.

2003· article· en· W2400786048 on OpenAlexaffabout
Neville Suskin, Susan Macdonald, Terri Swabey, Heather M. Arthur, Mark A. Vimr, Ravi Tihaliani

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineRehabilitationSecondary preventionChristian ministryPosition (finance)NursingFamily medicinePhysical therapyFinanceBusinessPolitical science
DOInot available

Abstract

fetched live from OpenAlex

The Cardiac Care Network of Ontario Consensus Panel on Cardiac Rehabilitation and Secondary Prevention drew on the literature and its own expertise, and surveyed existing cardiac rehabilitation and secondary prevention (CR) services in Ontario to make recommendations for the delivery of CR services in Ontario. This report, which is not an official position paper for the Canadian Cardiovascular Society, presents these recommendations. The key recommendations were a regional coordination model for the delivery of CR services that would provide CR close to home and promote access to CR in groups traditionally underrepresented in CR; high quality central data collection; the creation of a provincial CR registry to allow future planning, coordination, monitoring and evaluation of CR services in Ontario; and the establishment of specific CR program funding from the Ontario Ministry of Health and Long Term Care.

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)0.027
metaresearch head score (Gemma)0.024
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: Other · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score0.386

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.007
Science and technology studies0.0040.002
Scholarly communication0.0030.002
Open science0.0060.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.057
GPT teacher head0.349
Teacher spread0.292 · 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
GenreOther

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

Citations26
Published2003
Admission routes2
Has abstractyes

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