Processus d’implantation d’infirmières pivots en oncologie au sein d’équipes locales conjointes (Centre hospitalier-Communauté)
Bibliographic record
Abstract
Implementing oncology nurse navigators or IPOs (which stands for "infirmière pivot en oncologie") is a key element of the Québec Cancer Control Program in order to improve the continuity of care. This qualitative study describes the process of implementing IPOs in teams working both in hospitals and in the community. Several groups of stakeholders (IPOs, physicians, nurses, various health workers, administrators, people with cancer and their families) described how they perceive the functions and effects related to this implementation. After putting results into perspective, we recommend developing measures promoting the dissemination of the role and integration of IPOs in formally defined health teams. We strongly advocate for the continuation of joint efforts in order to define and clarify this complex role.
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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 | 0.026 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".