Bibliographic record
Abstract
Purpose: This methodological study translated, adapted, and validated the evidence based guideline of RNAO (Registered Nurses Association of Ontario) in Canada, for acute stroke care to domestic circumstances. Methods: Quality of the RNAO guideline was evaluated using AGREE tool. Then the guideline was translated into Korean and a preliminary guideline was established After checking content validation by an expert group,the Korean version of the guideline was applied to clinical settings to see its applicability. Results: The RNAO guideline in Korea was deemed appropriate. The Korean version of the guideline was drawn up with 56 items in 3 areas in stroke system related nursing, nursing of acute stroke inpatients, and stroke nursing assessment. A questionnaire survey was performed on appropriateness, enforceability, and applicability of those recommendations. A total of 54 recommendations were finalized after deleting 2 items below CVI 0.7 and correcting 3 items by taking professional advices. After trial application of the guideline to 40 stroke patients hospitalized at a ward of a hospital in Seoul, its performance was improved but was not statistically significant. Conclusion: This guideline is expected to contribute to improving nursing quality by offering it as a guide to evidence based practices for acute stroke care in Korea.
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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 | 0.035 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".