Translating Knowledge: A Framework for Evidence-Informed Yoga Programs in Oncology
Bibliographic record
Abstract
Empirical research suggests that yoga may positively influence the negative psychosocial and physical side effects associated with cancer and its treatment. The translation of these findings into sustainable, evidence-informed yoga programming for cancer survivors has lagged behind the research. This article provides (a) an overview of the yoga and cancer research, (b) a framework for successfully developing and delivering yoga to cancer populations, and (c) an example of a successful community-based program. The importance of continued research and knowledge translation efforts in the context of yoga and integrative oncology are highlighted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.130 | 0.071 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.016 | 0.009 |
| Science and technology studies | 0.007 | 0.036 |
| Scholarly communication | 0.021 | 0.016 |
| Open science | 0.011 | 0.021 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".