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Record W4367307253 · doi:10.1097/txd.0000000000001351

International Donation and Transplantation Legislative and Policy Forum: Methods and Purpose

2023· article· en· W4367307253 on OpenAlexafffundabout
Matthew J. Weiss, Marcelo Cantarovich, Prosanto Chaudhury, Mélanie Dieudé, David Hartell, Annie-Carole Martel, Chelsea Patriquin, Sam D. Shemie, Marie-Josée Simard, Jennifer Woolfsmith, Francis L. Delmonico, Beatriz Domínguez‐Gil

Bibliographic record

VenueTransplantation Direct · 2023
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsCanadian Patient Safety InstituteCanadian Blood ServicesUniversité de MontréalCentre Hospitalier de l’Université de MontréalHôpital de l'Enfant-JésusHéma-QuébecMcGill University Health CentreTranslational Research in Oncology
FundersHealth CanadaCanadian Blood Services
KeywordsMedicineLegislatureDonationTransplantationLawPolitical scienceSurgery

Abstract

fetched live from OpenAlex

Organ and tissue donation and transplantation (OTDT) legislation and policies vary around the world, and this variability contributes to discrepancies in system performance. This article describes the purpose and methodology of an international forum that was organized to create consensus recommendations related to key legal and policy attributes of an ideal OTDT system. The intent is to create guidance for legislators, regulators, and other system stakeholders who aim to create or reform OTDT legislation and policy. Methods: This Forum was initiated by Transplant Québec and cohosted by the Canadian Donation and Transplantation Program partnered with multiple national and international donation and transplantation organizations. Seven domains were identified by the scientific committee' and domain working groups identified specific topics for recommendations: Baseline Ethical Principles, Legal Foundations, Consent Model and Emerging Legal Issues, Donation System Architecture, Living Donation, Tissue Donation, and Research and Innovation Systems and Emerging Issues. Patient, family, and donor partners were integrated into every stage of the planning and execution of the Forum. Sixty-one participants from 13 countries contributed to recommendation generation. Topic identification and recommendation consensus was completed over a series of virtual meetings from March to September 2021. Consensus was achieved by applying the nominal group technique informed by literature reviews performed by participants. Recommendations were presented at a hybrid in-person and virtual forum in Montreal, Canada, in October 2021. Output: Ninety-four recommendations (9-33 per domain) and an ethical framework for evaluating new policies were developed during the Forum proceedings. The accompanying articles include the recommendations from each domain and justifications that link the consensus to existing literature and ethical or legal concepts. Conclusions: Although the recommendations could not account for the vast global diversity of populations, healthcare infrastructure, and resources available to OTDT systems, they were written to be as widely applicable as possible.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score0.745

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.363
Teacher spread0.339 · 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 teacher head, 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

Citations12
Published2023
Admission routes3
Has abstractyes

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