Cancer survivorship in the Western Pacific: from differences to shared-goals and from challenges to opportunities
Bibliographic record
Abstract
The Western Pacific region consists of 38 countries and approximately one quarter of the world population. Over 17 million people in the region have a personal history of cancer, necessitating effective survivorship care approaches for optimal outcomes and experiences. There are substantial differences in population and income and resource availability between countries within the region which impacts cancer survivorship care. Likewise, varying healthcare systems and models of survivorship care (e.g., primary care-led, patient-led etc.) affect the survivorship experience and outcome of people affected by cancer. Despite differences across Western Pacific countries, issues facing cancer survivors are similar, with shared challenges including lack of focus on survivorship care, adoption of a holistic approach, and workforce availability. Various approaches to cancer survivorship are being developed and implemented across the region, but a region-wide, coordinated approach is needed, involving thoughtful leadership and sharing of ideas to achieve better outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".