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Record W2061892723 · doi:10.1249/jsr.0b013e3181ae98f3

Effects of Exercise on Quality of Life and Prognosis in Cancer Survivors

2009· review· en· W2061892723 on OpenAlexafffund
Amy E. Speed-Andrews, Kerry S. Courneya

Bibliographic record

VenueCurrent Sports Medicine Reports · 2009
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Alberta
FundersCanada Research Chairs
KeywordsMedicineQuality of life (healthcare)Survivorship curveCancer survivorshipObservational studyDiseaseCancerPalliative careMEDLINEGerontologyPhysical therapyIntensive care medicineInternal medicineNursing

Abstract

fetched live from OpenAlex

Cancer is a global health problem with over 10 million cancer survivors in the United States alone. Cancer and its treatments often produce side effects that undermine quality of life. The purpose of this article is to review research examining the effects of physical activity (PA) upon quality of life and disease prognosis in cancer survivors. We divide our review into PA studies focusing upon (a) quality of life during treatments, (b) quality of life during survivorship (after treatments), (c) quality of life during palliative care, and (d) disease prognosis end points. Compelling clinical trial data indicate that PA can improve quality of life end points during treatment and survivorship. Data during palliative care is limited. Observational data suggest that PA may reduce the risk of disease recurrence and extend survival in some cancer survivors. Research findings suggest that PA is an appropriate recommendation for most cancer survivors, although many research questions remain.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.068
GPT teacher head0.404
Teacher spread0.336 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations75
Published2009
Admission routes2
Has abstractyes

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