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Record W2423032730

...that exercise training is safe, useful and effective therapy and does not worsen cardiac function in heart failure?

2011· article· en· W2423032730 on OpenAlexaff
E. Estrella-Holder

Bibliographic record

VenuePubMed · 2011
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsSt. Boniface Hospital
Fundersnot available
KeywordsHeart failureMedicineRehabilitationExercise therapyCardiac function curvePhysical therapyTraining (meteorology)Intensive care medicinePhysical exercisePhysical medicine and rehabilitationCardiologyInternal medicineRandomized controlled trial
DOInot available

Abstract

fetched live from OpenAlex

Exercise training in heart failure is safe, useful and effective therapy in the management of heart failure patients. Contrary to the old belief, it does not worsen cardiac function. Smaller studies also reported reduction in mortality and morbidity associated with exercise training. The available data support training HF patients to improve exercise tolerance and symptoms. Patients should be properly reviewed by their physicians prior to engaging in exercise training. It is highly recommended that patients be referred to a cardiac rehabilitation program, especially those with severe or advanced heart failure.

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)0.006
metaresearch head score (Gemma)0.022
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0170.007

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 head0.036
GPT teacher head0.215
Teacher spread0.180 · 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

Citations2
Published2011
Admission routes1
Has abstractyes

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