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Record W7030379256

Medical Certificates of Death: First Principles and Established Practice Provide Answers to New Questions

2016· article· en· W7030379256 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2016
Typearticle
Languageen
FieldMedicine
TopicAutopsy Techniques and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsDeath certificateLegislationSupreme courtSubject (documents)Antecedent (behavioral psychology)Medical practice
DOInot available

Abstract

fetched live from OpenAlex

Voluntary euthanasia became legal in Quebec in December 2015,1 although the legislation is currently the subject of litigation. In addition, physician-assisted death will become legal across Canada in February 2016,2 barring an extension on the deadline being given by the Supreme Court of Canada. There are many questions about how physician-assisted death should be regulated. One as-yet-unanswered question is “Should physician-assisted death be recorded anywhere on the medical certificate of death?” If so, a second question follows: “How should it be recorded — as manner and/or cause?” and if the latter, “Which category of cause: immediate, antecedent or underlying?” To address these questions, we reviewed the purposes of medical certificates of death, the various medical certificates of death in use across Canada, death certificates in jurisdictions that already permit physician-assisted death and the law with respect to life insurance in Canada and abroad. We found that, by turning to first principles and established practices regarding completion of medical certificates of death, we were able to find sensible answers to these questions.

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)0.160
metaresearch head score (Gemma)0.355
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.160
Threshold uncertainty score0.846

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1600.355
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0060.040
Scholarly communication0.0110.019
Open science0.0050.006
Research integrity0.0090.022
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.028
GPT teacher head0.306
Teacher spread0.277 · 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
Published2016
Admission routes1
Has abstractyes

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