CANO-ACIO/ONS/ISNCC JOINT SYMPOSIUM AT THE CANO-ACIO CONFERENCE IN CALGARY ALBERTA: Global perspectives on cancer survivorship: From lost in transition to leading into the future
Bibliographic record
Abstract
In the decade since the Institute of Medicine’s 2006 landmark report, entitled From cancer patient to cancer survivor: Lost in transition, cancer survivorship increasingly has become a distinct phase in the cancer journey. While much progress has been made toward creating a system of care that optimally addresses survivors’ needs, significant gaps remain. An international symposium to discuss and explore global challenges in cancer survivorship care was held at the Canadian Association of Nurses in Oncology (CANO/ACIO) conference in Calgary, Alberta, in October 2016. In this paper, we summarize presentations from that symposium, exploring cancer survivorship care from Canadian, American, and International perspectives, and describing challenges, issues and gaps. Strategies are also discussed for oncology nurses, individually and collectively, to provide future leadership in shaping survivorship care to be more person centered and equity oriented.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.038 | 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".