Bibliographic record
Abstract
EBN Perspectives brings together key issues from the commentaries in one of our nursing topic themes. This article is part of Evidence Based Nursing (EBN) Perspectives . In this series, commentaries from the past 2 years from a specific nursing theme are brought together and highlights are discussed. The topic for this edition is advance care planning and palliative care. From October 2014 to the October 2016 edition, 12 commentaries were published on the chosen topic. Key themes are extrapolated from these commentaries, and the implications for practice and future research are explored. The 12 commentaries are presented in box 1 and grouped into themes of patient and family/loved ones involvement; nursing advocacy; healthcare processes. Box 1 ### Evidence Based Nursing commentaries on advance care planning and palliative care (October 2014–October 2016) Themes: patient and family involvement; nurse as advocate for patient at end-of-life and processes for implementation of advance care planning (ACP) and palliative care Theme 1: Patient and family/loved ones involvement 1. Threats to parents' roles during the process of their child dying in the paediatric intensive care unit http://ebn.bmj.com/content/19/4/118.extract 2. What ‘a good death’ means for bereaved family carers http://ebn.bmj.com/content/19/2/59.extract 3. Carers providing end-of-life care at home have limited formal support in managing medications http://ebn.bmj.com/content/18/4/115.extract 4. Clarification of the common aspects of dignity in end-of-life care http://ebn.bmj.com/content/18/3/76.extract 5. Home death versus hospital death: …
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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 | 0.027 | 0.136 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.007 | 0.017 |
| Insufficient payload (model declined to judge) | 0.036 | 0.006 |
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".