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Record W4412851886 · doi:10.1016/j.ajt.2025.07.1215

Sexual Orientation and Gender Identity Data Collection in Solid Organ Transplant Programs in the United States

2025· article· en· W4412851886 on OpenAlexaff
Pei‐Jer Chen, Marc-Henry Wakim, Dang Quang Dinh, M. Kurtca, Felice Cinque, Newsha Nikzad, Apaar Dadlani, Ligia Sierra, Thu T. Nguyen, Shelby A. Smout, Nandita Singh, Alexandra T. Strauss, Ken Sutha, Ashish Patel, Jennifer Trofe‐Clark, Murdoch Leeies, T. Lee

Bibliographic record

VenueAmerican Journal of Transplantation · 2025
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineSexual orientationGender identitySolid organOrgan transplantationSexual identityOrientation (vector space)TransplantationSocial psychologyInternal medicineHuman sexualityGender studiesPsychology

Abstract

fetched live from OpenAlex

Purpose: Sexual orientation and gender identity (SOGI) data are integral in providing personalized transplant care. Our study aimed to assess the SOGI data collection in US transplant programs and identify potential benefits, harms, and barriers.

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)0.005
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.404
Teacher spread0.334 · 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

Citations0
Published2025
Admission routes1
Has abstractno

Explore more

Same venueAmerican Journal of Transplantation→Same topicLGBTQ Health, Identity, and Policy→French-language works237,207→