Letter to the Editor: The development of knights cabin cancer retreats: a community program to engage cancer survivors’ proactive health behaviors
Bibliographic record
Abstract
Abstract Purpose Cancer survivors often lack the knowledge and skills to return to positive health behaviors following a cancer diagnosis. The use of retreats may be an ideal environment for cancer survivors to learn about health behaviours while receiving social support from other survivors. Methods Knights Cabin Cancer Retreats was created as a charitable organization in 2014 and is at no cost to participants or their supporters. Elements of the retreat include guided hikes, yoga, classes on nutrition, stress, mindfulness and sleep management techniques, all with a focus on the evidence based theories of behavioral change. Results Ten retreats have been hosted across Canada to date with 137 cancer survivors and their supporters. Survivors reported that their top learning outcomes from the retreat were physical activity/nutrition and behavioral change/habit development. Conclusion Knight’s Cabin Cancer retreats are unique in their programming with a format of health education that allows for emotional support and engagement with other cancer survivors in a therapeutically natural environment.
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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 | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.015 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".