Redefining the primary nurse role in oncology care: A 21st century perspective
Bibliographic record
Abstract
Oncology nursing is a rapidly evolving specialty with increasing demands upon nurses to respond to the complex needs of cancer patients and their families. Primary nursing (PN) has been the model of care delivery utilized at our cancer centre for more than two decades. The nursing department determined it was time that a review and redefining of the role be undertaken. These objectives were achieved through the implementation of the Primary Nurse Role Development Project. This article discusses: a brief background of why the existing role needed to be reviewed and revised; an overview of how primary nursing has been applied historically at the centre; and details regarding the project plan and its implementation. Results from the project provided a competency-based oncology primary nurse role description, which will be outlined along with proposals for improving nursing practice. Our goal is to achieve optimal care for our patients.
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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 | 0.020 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.020 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".