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Record W2989834402 · doi:10.1111/nin.12321

Palliative sedation and medical assistance in dying: Distinctly different or simply semantics?

2019· article· en· W2989834402 on OpenAlexaffabout
Reanne Booker, Anne Bruce

Bibliographic record

VenueNursing Inquiry · 2019
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of VictoriaAlberta Health Services
Fundersnot available
KeywordsPalliative careRelevance (law)Palliative sedationSedationPsychologyNursingQuality of life (healthcare)Quality (philosophy)MedicinePsychiatryLawPolitical scienceEpistemologyPharmacologyPhilosophy

Abstract

fetched live from OpenAlex

Medical assistance in dying (MAiD) and palliative sedation (PS) are both legal options in Canada that may be considered by patients experiencing intolerable and unmanageable suffering. A contentious, lively debate has been ongoing in the literature regarding the similarities and differences between MAiD and PS. The aim of this paper is to explore the propositions that MAiD and PS are essentially similar and conversely that MAiD and PS are distinctly different. The relevance of such a debate is apparent for clinicians and patients alike. Understanding the complex and multi-faceted nuances between PS and MAiD allows patients and caregivers to make more informed decisions pertaining to end-of-life care. It is hoped that this paper will also serve to foster further debate and consideration of the issues associated with PS and MAiD with a view to improve patient care and the quality of both living and dying in Canada.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.145
Threshold uncertainty score0.288

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0060.066
Scholarly communication0.0120.012
Open science0.0020.006
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.148
GPT teacher head0.446
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations22
Published2019
Admission routes2
Has abstractyes

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