A framework for prescription in exercise‐oncology research
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.
Bibliographic record
Abstract
The field of exercise-oncology has increased dramatically over the past two decades, with close to 100 published studies investigating the efficacy of structured exercise training interventions in patients with cancer. Of interest, despite considerable differences in study population and primary study end point, the vast majority of studies have tested the efficacy of an exercise prescription that adhered to traditional guidelines consisting of either supervised or home-based endurance (aerobic) training or endurance training combined with resistance training, prescribed at a moderate intensity (50-75% of a predetermined physiological parameter, typically age-predicted heart rate maximum or reserve), for two to three sessions per week, for 10 to 60 min per exercise session, for 12 to 15 weeks. The use of generic exercise prescriptions may, however, be masking the full therapeutic potential of exercise treatment in the oncology setting. Against this background, this opinion paper provides an overview of the fundamental tenets of human exercise physiology known as the principles of training, with specific application of these principles in the design and conduct of clinical trials in exercise-oncology research. We contend that the application of these guidelines will ensure continued progress in the field while optimizing the safety and efficacy of exercise treatment following a cancer diagnosis.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it