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History informing the future of exercise oncology

2025· article· en· W4413332200 on OpenAlexaff
Daniel A. Galvão, Kerry S. Courneya, Alejandro Lucía, Anne M. May, Karen M. Mustian, Allison Betof Warner, Wiskemann Joachim, Karen Y. Wonders, Kathryn H. Schmitz, Robert U. Newton

Bibliographic record

VenueJNCI Monographs · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsInstitute of Cancer ResearchUniversity of Alberta
FundersEdith Cowan University
KeywordsMedicineOncologyInternal medicineMedical physics

Abstract

fetched live from OpenAlex

Exercise is increasingly recognized by patients, clinicians, and allied health professionals globally as an important component of cancer care. In this paper, we provide a viewpoint on developments in exercise oncology over the past 4 decades leading up to the creation of the International Society of Exercise Oncology (ISEO). We briefly review research in adult and pediatric cancers from early foundation studies to larger randomized controlled trials published in mainstream oncology journals alongside critical work undertaken in exercise and cancer biological mechanisms. We also discuss potential strengths, weaknesses, opportunities, and threats facing ISEO in becoming a global forum for exercise oncology. Building on the foundational work undertaken over the past 4 decades by researchers, clinicians, and practitioners, ISEO provides an opportunity to support research, leverage collaborations and partnerships, facilitate education and training, increase awareness of exercise oncology, and support translation of research to clinical practice, ultimately improving the quality and quantity of life for people with 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)0.013
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: Commentary · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.007
Scholarly communication0.0050.007
Open science0.0010.003
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0100.002

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 head0.011
GPT teacher head0.272
Teacher spread0.260 · 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
GenreCommentary

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

Citations7
Published2025
Admission routes1
Has abstractyes

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