18 Best Practice Nursing Care across the Stroke Continuum: Recommendations for Assessment and Management
Bibliographic record
Abstract
Purpose: The purpose of this presentation is to discuss the development, pilot testing, and national roll-out of a Stroke Best Practices Nursing Workshop developed by the National Stroke Nursing Council (NSNC) of the Canadian Stroke Network (CSN). The NSNC was established in 2005 to promote leadership, communication, advocacy, education and nursing research in the field of stroke, and to support the vision of the Canadian Stroke Strategy to have an integrated and coordinated approach to stroke prevention, treatment, rehabilitation and community integration in every province and territory in Canada. The council works to build understanding of the critical role of Canadian stroke nurses, to give a voice to experiences on the frontline and to facilitate the dissemination and application of best practices. In keeping with this mandate, in 2008 the NSNC developed a stroke nursing workshop entitled Best Practice Nursing Care across the Acute Stroke Continuum: Recommendations for Assessment and Management.
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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 | 0.048 | 0.079 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.009 | 0.010 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 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".