Transforming Community Cancer Care: The Ottawa Regional Cancer Foundation’s Cancer Coaching Practice
Bibliographic record
Abstract
Community services are an increasingly important part of the healthcare landscape. Services that work to empower patients and their caregivers are having a positive impact on health outcomes and helping to reduce per capita costs of healthcare. According to the 2015 Canadian Cancer Statistics Report, by 2030 the annual number of new cancer cases in Canada is expected to increase by 79% [1]. Community-based cancer services, in particular, are urgently required to meet the growing demand for care as the complexity of the disease and its treatment continues to grow. RÉSUMÉ Les services communautaires jouent un rôle de plus en plus important dans les soins de santé. Les services qui veillent à habiliter les patients et leurs proches aidants ont un effet positif sur les résultats en matière de santé et aident à réduire les coûts par personne des soins de santé. D’ici 2030, le nombre annuel de nouveaux cas de cancer au Canada devrait augmenter de 79 % selon le rapport Statistiques canadiennes sur le cancer 2015 [1]. Des services communautaires pour le traitement du cancer, notamment, sont requis de toute urgence afin de répondre à la demande croissante de soins, alors que la complexité de la maladie et de son traitement ne cesse de croître.
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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 | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.006 | 0.015 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".