MétaCan
Menu
Back to cohort
Record W2106011651 · doi:10.3747/co.19.912

Exercise in Clinical Cancer Care: A Call to Action and Program Development Description

2012· article· en· W2106011651 on OpenAlexaffvenueabout
Daniel Santa Mina, Shabbir M.H. Alibhai, A. Matthew, Crissa L. Guglietti, Julie R. Steele, John Trachtenberg, Paul G. Ritvo

Bibliographic record

VenueCurrent Oncology · 2012
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity Health NetworkPrincess Margaret Cancer CentreYork University
Fundersnot available
KeywordsMedicineCall to actionCancerExperiential learningAction (physics)Physical therapyPsychologyInternal medicine

Abstract

fetched live from OpenAlex

A large and convincing body of evidence demonstrates the benefits of exercise for cancer survivors during and after treatment. Based on that literature, more cancer survivors should be offered exercise support and programming. Unfortunately, exercise programs remain an exception rather than the norm in cancer care. Not surprisingly, common barriers to the implementation of exercise programs in oncology include limited resources, expertise, and awareness of benefits on the part of patients and clinicians. To improve the accessibility and cost-effectiveness of cancer exercise programs, one proposed strategy is to combine the resources of hospital and community-based programs with home-based exercise instruction. The present paper highlights current literature regarding exercise programming for cancer survivors, describes the development of an exercise program for cancer patients in Toronto, Canada, and offers experiential insights into the integration of exercise into oncologic 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

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

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 head0.254
GPT teacher head0.513
Teacher spread0.259 · 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 teacher head, 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

Citations82
Published2012
Admission routes3
Has abstractyes

Explore more

Same venueCurrent OncologySame topicCancer survivorship and careFrench-language works237,207