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Record W2087263257 · doi:10.1097/tp.0b013e3181a4eae5

Discovering Misattributed Paternity in Living Kidney Donation

2009· article· en· W2087263257 on OpenAlexafffundabout
Ann Young, S. Joseph Kim, Eric M. Gibney, Chirag R. Parikh, Meaghan S. Cuerden, Lucy D. Horvat, Patricia Hizo-Abes, Amit X. Garg

Bibliographic record

VenueTransplantation · 2009
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsLondon Health Sciences CentreUniversity of TorontoUniversity Health NetworkWestern University
FundersU.S. Public Health ServiceLondon Health Sciences Centre
KeywordsDonationOrgan donationFamily medicineKidney donationPreferenceMedicineInformation sharingKidney transplantationTransplantationLawInternal medicine

Abstract

fetched live from OpenAlex

When evaluating a living kidney donor and recipient with a father-child relationship, it may be discovered that the two are not biologically related. We analyzed data from the United Network for Organ Sharing and the Canadian Organ Replacement Registry to determine how frequently this occurs. We surveyed 102 potential donors, recipients, and transplant professionals for their opinion on whether such information should be disclosed to the donor-recipient pair. We communicated with transplant professionals from 13 Canadian centers on current practices for handling this information. In the United States and Canada, the prevalence of father-child living kidney donor-recipient pairs with less than a one-haplotype human leukocyte antigen match (i.e., misattributed paternity) is between 1% and 3%, or approximately 0.25% to 0.5% of all living kidney donations. Opinions about revealing this information were variable: 23% strongly favored disclosure; whereas, 24% were strongly opposed to it. Current practices are variable; some centers disclose this information, whereas others do not. Discovering misattributed paternity in living donation is uncommon but can occur. Opinions on how to deal with this sensitive information are variable. Discussion among transplant professionals will facilitate best practices and policies. Strategies adopted by some centers can be considered.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.013
GPT teacher head0.265
Teacher spread0.251 · 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

Citations35
Published2009
Admission routes3
Has abstractyes

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