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Record W3174556557 · doi:10.1002/pmrj.12664

Translating<scp>2019 ACSM</scp>Cancer Exercise Recommendations for a Physiatric Practice: Derived Recommendations from an International Expert Panel

2021· review· en· W3174556557 on OpenAlexaff
Sara C. Parke, Amy Ng, Patrick Martone, Lynn H. Gerber, David S. Zucker, Jessica Engle, Ekta Gupta, Katherine Power, Jonas Sokolof, Samman Shahpar, Leslie Bagay, Bruce E. Becker, David M. Langelier

Bibliographic record

VenuePM&R · 2021
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsSports medicineRehabilitationMedicineFamily medicineMEDLINEPhysical therapyMedical educationCancerGerontology

Abstract

fetched live from OpenAlex

In 2018, the American College of Sports Medicine (ACSM) reconvened an international, multi-disciplinary group of professionals to review pertinent published literature on exercise for people with cancer. The 2018 roundtable resulted in the publication of three articles in 2019. The three articles serve as an important update to the original ACSM Roundtable on Cancer, which convened in 2010. Although the focus of the three 2019 articles is on exercise, which is only one part of comprehensive cancer rehabilitation, the evidence presented in the 2019 ACSM articles has direct implications for physiatrists and other rehabilitation professionals who care for people with cancer. As such, the narrative review presented here has two primary objectives. First, we summarize the evidence within the three ACSM articles and interpret it within a familiar rehabilitation framework, namely the Dietz model of Cancer Rehabilitation, in order to facilitate implementation broadly within rehabilitation practice. Second, via expert consensus, we have tabulated relevant exercise recommendations for specific cancer populations at different points in the cancer care continuum and translated them into text, tables, and figures for ease of reference. Notably, the authors of this article are members of the Cancer Rehabilitation Physician Consortium (CRPC), a group of physicians who subspecialize in cancer rehabilitation medicine (CRM).

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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.954
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.130
GPT teacher head0.441
Teacher spread0.311 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations10
Published2021
Admission routes1
Has abstractyes

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