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Record W2995813872

[Organ donor families should be free to meet their recipients under controlled conditions if both sides wish, Italian National Committee for Bioethics says (Italian translation by A. Scarabelli)].

2019· article· it· W2995813872 on OpenAlexaff
Carlo Petrini, Reginald Green, Andrea Scarabelli

Bibliographic record

VenuePubMed · 2019
Typearticle
Languageit
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsGreenField Specialty Alcolhols (Canada)
Fundersnot available
KeywordsBioethicsObligationLawWishOrder (exchange)Political scienceAnonymityLegalizationSociologyMedicineFamily medicineBusiness
DOInot available

Abstract

fetched live from OpenAlex

On 27 September 2018 the Italian Committee for Bioethics (ICB) adopted an opinion regarding the possibility of an exception to the anonymity obligation when both parties agree and have signed an appropriate informed consent form. According to the IBC any contact between the donor's family and recipient must be managed by a third-party body pertaining to the National Health Service, established to guarantee strict control over the expression of consent in order to avoid any risk of inappropriate behaviour. The paper traces how Reg and Maggie Green, on holiday from California, donated the organs of their seven-year old son, Nicholas, to seven Italians after he had been shot in a carjacking on the Salerno-Reggio Calabria highway in 1994. Reluctant as a foreigner to propose a change in Italian law that effectively prevents the two sides from contacting each other, Reg Green held back for 22 years until, at age 87, he began a public campaign to voice his concern that the law was hurting transplant families rather than helping them. (This is the Italian translation of an article published in the Annali dell'Istituto Superiore di Sanità 2019; 55(1):6-9. https://doi.org/10.4415/ANN_19_01_03).

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)0.006
metaresearch head score (Gemma)0.016
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.035
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0100.013
Insufficient payload (model declined to judge)0.0290.031

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 head0.079
GPT teacher head0.303
Teacher spread0.224 · 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
GenreCommentary

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
Published2019
Admission routes1
Has abstractyes

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