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Record W2483944385 · doi:10.1111/ajt.13868

Living Organ Donation by Minors: An Analysis of the Regulations in European Union Member States

2016· article· en· W2483944385 on OpenAlexaboutno aff
Kristof Thys, Kristof Van Assche, Herman Nys, Sigrid Sterckx, Pascal Borry

Bibliographic record

VenueAmerican Journal of Transplantation · 2016
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMember statesOrgan donationEuropean unionDonationFamily medicineLawTransplantationSurgeryInternational tradePolitical science

Abstract

fetched live from OpenAlex

Living organ donation (LD) is an increasingly established practice. Whereas in the United States and Canada LD by minors has occasionally been reported, LD by minors seems to be largely absent in the European Union (EU). It is currently unclear whether this is the result of a different legal approach. This study is the first to systematically analyze the regulations of EU member states, Norway, and Iceland toward LD by minors. Relevant regulations were identified by searching government websites, translated, compared, and sent for verification to national legal experts. We identified five countries where LD by minors is allowed. In two of these (Belgium and the United Kingdom), some minors may be deemed sufficiently mature to make an autonomous decision regarding LD. In contrast, in the three other countries (Luxembourg, Norway, and Sweden), LD by minors is only allowed subject to parental permission and the assent (or absence of objection) of the donor. Where allowed, regulations differ significantly with regard to the substantive and procedural safeguards in place. In view of the controversial nature of the procedure, as illustrated by recent reports and surveys, we argue for a very cautious approach and greater harmonization in countries where LD by minors is allowed.

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)0.011
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.008
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.253
Teacher spread0.245 · 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 designObservational
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

Citations16
Published2016
Admission routes1
Has abstractyes

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