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Record W4410202373 · doi:10.7202/1117879ar

Why Not Advance Directives for MAID in Those with Dementia?

2025· article· en· W4410202373 on OpenAlexaffvenue
Michael Gordon

Bibliographic record

VenueCanadian Journal of Bioethics · 2025
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDementiaMEDLINEBusinessComputer scienceMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

The numbers of individuals with Alzheimer’s disease and other dementias are growing rapidly in North America and the rest of the western world. In most jurisdictions there is a major societal challenge to provide appropriate care for these individuals as well as their families. At present in North America, it is not possible for a person with dementia, while anticipating the declining trajectory of their disabling illness, to indicate to their substitute decision makers (SDM or proxies in the USA) a request for medical assistance in dying (MAID). This is the case even if at the time of making the request the person is legally capable of taking such a decision using the criteria for MAID in other clinical situations. The question is why a person with Alzheimer’s disease or other causes of dementia should not be able to anticipate their decline while still capable. And if so, to instruct their designated decision-maker to request and obtain MAID, their indicated preference in a legal advance directive.

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)0.044
metaresearch head score (Gemma)0.163
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.233

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.163
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0070.013
Scholarly communication0.0060.010
Open science0.0030.004
Research integrity0.0150.024
Insufficient payload (model declined to judge)0.0060.003

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 head0.145
GPT teacher head0.438
Teacher spread0.293 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes2
Has abstractyes

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