MétaCan
Menu
Back to cohort
Record W2140659195 · doi:10.3747/co.21.2079

Design and Implementation of a Community-Based Exercise Program for Breast Cancer Patients

2014· article· en· W2140659195 on OpenAlexaffvenue
Heather J. Leach, Jessica Danyluk, S. Nicole Culos‐Reed

Bibliographic record

VenueCurrent Oncology · 2014
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineBreast cancerCancerPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Research has indicated that exercise is critical in the recovery process for breast cancer patients, and yet this evidence has infrequently been translated into sustainable community programming. The present article describes the processes and operations of beauty (the Breast Cancer Patients Engaging in Activity and Undergoing Treatment program). This evidence-based 12-week exercise program, with an optional 12-week maintenance component, is supported by the Wings of Hope Foundation, allowing the program to be delivered at no cost to participants. The program was designed to restore and improve the physical well-being of women living with breast cancer as they undergo chemotherapy or radiation treatments. Evaluations measure safety and adherence to the program and the effects of the program on physiologic and psychological outcomes and quality of life. The beauty program addresses the gap between the level of evidence for the benefits of exercise after a cancer diagnosis and translation of that evidence into community programming by providing an accessible, individualized, and safe physical activity program for women during treatment for breast cancer.

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)0.007
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: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.090
GPT teacher head0.444
Teacher spread0.354 · 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

Citations36
Published2014
Admission routes2
Has abstractyes

Explore more

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