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Record W2983374065 · doi:10.1186/s41241-019-0083-2

Letter to the Editor: The development of knights cabin cancer retreats: a community program to engage cancer survivors’ proactive health behaviors

2019· letter· en· W2983374065 on OpenAlexaffabout
Iris Lesser, Erin McGowan, Lisa J. Bélanger

Bibliographic record

VenueApplied cancer research/Applied Cancer Research · 2019
Typeletter
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of CalgaryMemorial University of NewfoundlandUniversity of the Fraser Valley
Fundersnot available
KeywordsKnightHabitCancerMedicineGerontologyPsychologySocial psychology

Abstract

fetched live from OpenAlex

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.

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)0.018
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.007
Science and technology studies0.0050.002
Scholarly communication0.0010.000
Open science0.0060.003
Research integrity0.0020.032
Insufficient payload (model declined to judge)0.0020.000

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 head0.163
GPT teacher head0.464
Teacher spread0.301 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2019
Admission routes2
Has abstractyes

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