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Record W4226000154 · doi:10.7202/1084453ar

Advanced Requests for MAID: Are They Compatible with Canadian Medical Practice?

2021· article· en· W4226000154 on OpenAlexaffvenueabout
James Mellett, Cheryl Mack, Brendan Leier

Bibliographic record

VenueCanadian Journal of Bioethics · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLegislatureMedical practicePolitical scienceLawMedicineFamily medicine

Abstract

fetched live from OpenAlex

The recent passing of Bill C-7 has placed Advance Requests for MAID (ARMs) on Canada’s legislative agenda. We discuss how ARMs may create ethical and practical challenges for Canadian medical practice.

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)0.201
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: Empirical · Consensus signal: none
Teacher disagreement score0.125
Threshold uncertainty score0.542

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.201
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0180.017
Scholarly communication0.0180.009
Open science0.0050.006
Research integrity0.0200.021
Insufficient payload (model declined to judge)0.0150.002

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 head0.121
GPT teacher head0.471
Teacher spread0.350 · 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
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

Citations2
Published2021
Admission routes3
Has abstractyes

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Same venueCanadian Journal of BioethicsSame topicMedical Malpractice and Liability IssuesFrench-language works237,207