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Record W3033243245 · doi:10.1002/9781119568124.ch43

Physical Activity and Recovery from Breast Cancer

2020· other· en· W3033243245 on OpenAlexaff
Meghan H. McDonough, S. Nicole Culos‐Reed

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychological interventionBreast cancerSurvivorship curveMental healthPsychologyQuality of life (healthcare)Physical activityPopulationSocial supportGerontologyMedicinePsychotherapistCancerPhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

Physical activity is an important consideration for breast cancer survivors as research has elucidated a variety of psychological, social, and physical benefits of being active during and post-treatment. Considerable research in exercise psychology is focused on the psychological, social, and quality-of-life effects of exercise and physical activity in this population. Research also includes testing exercise programs and behavior change interventions to improve the adoption, adherence, and maintenance of physical activity behavior throughout the survivorship continuum; and translation of this knowledge into practice in healthcare and community settings. Physical activity can reduce stress, maintain or improve mental health, and facilitate psychological growth in the wake of cancer. Social support and camaraderie gained through group physical activity programs may play a role in helping participants cope with the disease. A meta-analysis has demonstrated that exercise interventions significantly improve body image.

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)0.003
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.013
GPT teacher head0.271
Teacher spread0.258 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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