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Record W4387710066 · doi:10.1016/j.jaccao.2023.08.008

Incorporating Exercise Training into Cardio-Oncology Care

2023· review· en· W4387710066 on OpenAlex

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

VenueJACC CardioOncology · 2023
Typereview
Languageen
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsToronto General HospitalTed Rogers Centre for Heart Research
FundersNational Cancer InstituteMemorial Sloan-Kettering Cancer Center
KeywordsMedicineSurvivorship curveIntensive care medicineCancerCancer survivorshipOncologyCancer treatmentInternal medicinePhysical therapy

Abstract

fetched live from OpenAlex

Cancer treatment-induced cardiotoxicities are an ongoing concern throughout the cancer care continuum from treatment initiation to survivorship. Several "standard-of-care" primary, secondary, and tertiary prevention strategies are available to prevent the development or further progression of cancer treatment-induced cardiotoxicities and their risk factors. Despite exercise's established benefits on the cardiovascular system, it has not been widely adopted as a nonpharmacologic cardioprotective strategy within cardio-oncology care. In this state-of-the-art review, the authors discuss cancer treatment-induced cardiotoxicities, review the existing evidence supporting the role of exercise in preventing and managing these sequelae in at-risk and affected individuals living after cancer diagnoses, and propose considerations for implementing exercise-based services in cardio-oncology practice.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0030.002
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 head0.137
GPT teacher head0.411
Teacher spread0.275 · 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