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Record W4392055693 · doi:10.1097/tp.0000000000004918

Transplantation in the Context of Migration and Refugees: A Summary of the DICG and TTS Ethics Committee Workshop, Buenos Aires, Argentina, September 2022

2024· article· en· W4392055693 on OpenAlexaff
Peter G. Stock, Sanjay Nagral, Éric Rondeau, Sylwia Gawrońska, Jennifer Groverman, A Barbari, P Coates, Beatriz Domínguez‐Gil, Riadh Fadhil, Jolanta Małyszko, Alejandro Niño Murcia

Bibliographic record

VenueTransplantation · 2024
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsMultiple Sclerosis Society of Canada
Fundersnot available
KeywordsRefugeeDeclarationTransplantationContext (archaeology)Political sciencePopulationHealth careEconomic growthMedicinePublic administrationLawGeographyEnvironmental health

Abstract

fetched live from OpenAlex

Global conflicts and humanitarian crises have resulted in an unprecedented number of refugees and migrants. This challenges the limited resources of health care systems and jeopardizes the availability of transplant care for these deserving migrants and refugees. This was the basis for a workshop held during the Congress of the Transplantation Society (Buenos Aires, 2022). We elaborate on the proceedings of the workshop entitled "Transplantation in the Context of Migration and Refugees," organized by the Ethics Committee of The Transplantation Society and Declaration of Istanbul Custodian Group. Transplant providers from around the world shared strategies of how each region has responded to providing access to care for refugees and migrants in need of transplant services. The potential exploitation of this vulnerable group leading to illicit organ removal was addressed for each region. The Transplantation Society, Declaration of Istanbul Custodian Group, and global transplant community should continue to focus on the status of refugees and migrants and collaborate on strategies to provide access to transplant care for this deserving population. Global cooperation will be essential to provide vigilant oversight to prevent exploitation of this vulnerable population.

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)0.001
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 score0.598
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.021
GPT teacher head0.298
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 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

Citations5
Published2024
Admission routes1
Has abstractyes

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