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Record W3121057218

Euthanasia by Organ Donation

2018· article· en· W3121057218 on OpenAlexaboutno aff
Michael Shapiro

Bibliographic record

VenueeYLS (Yale Law School) · 2018
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsnot available
Fundersnot available
KeywordsOrgan donationDonationMedicineMedical lawPolitical scienceLawTransplantationSurgery
DOInot available

Abstract

fetched live from OpenAlex

Euthanasia, the administration of therapy designed to hasten death, particularly in patients with intolerable suffering, has been gaining in acceptance in countries around the world, most recently in Canada. Organ donation from deceased organ donors has always been performed under the strictures of the dead donor rule, the requirement that donors be declared dead prior to any organ recovery. Recent scientific and ethical investigations, however, have questioned whether all donors, whether pronounced based on neurologic (brain death) or circulatory criteria are, in fact, dead. One potential approach to this quandary would be to abandon the fiction imposed by the dead donor rule and consider the possibility of organ donation as another mode of euthanasia. This approach would be much more precise philosophically, provide such donors with a "gooddeath" not always possible with current organ recovery techniques, and potentially also increase organ availability.

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)0.008
metaresearch head score (Gemma)0.011
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 score0.009
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0030.023
Scholarly communication0.0040.004
Open science0.0010.006
Research integrity0.0090.009
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 head0.017
GPT teacher head0.275
Teacher spread0.258 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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