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The multidisciplinary community of exercise oncology practice: current status and future directions

2025· article· en· W4413311567 on OpenAlex
Chao Cao, Kristin L. Campbell, Allison Betof Warner, Nancy Campbell, Anna L. Schwartz, Christine Cleary, Karen Y. Wonders, L Capozzi, Jennifer A. Ligibel

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJNCI Monographs · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of CalgaryUniversity of British Columbia
FundersNational Center for Research ResourcesNational Institute of Nursing ResearchNational Cancer InstituteNational Institute on Aging
KeywordsMultidisciplinary approachCurrent (fluid)MedicineMedical educationPsychologyOncologyEngineeringSociologySocial science

Abstract

fetched live from OpenAlex

Exercise is recommended as a part of standard cancer care, based upon its favorable impact on treatment-related side effects and its association with better cancer outcomes. Fully incorporating exercise into oncology practice will require multidisciplinary efforts across oncology and exercise professionals. This article examines current patterns of exercise advice and prescription in oncology settings and highlights the roles of oncology clinicians, physiatrists, physical and occupational therapists, exercise physiologists and fitness trainers, and patient advocates in expanding exercise oncology across the cancer continuum. Future efforts to enhance provider education, expand community-based programs, establish referral pathways, and address policy challenges related to reimbursement will be needed to establish exercise as a universally accessible and effective component of oncology 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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.907
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.363
Teacher spread0.344 · 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