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Record W2989764035 · doi:10.1089/trgh.2019.0026

Incorporating Transition-Affirming Language into Anatomical Pathology Reporting for Gender Affirmation Surgery

2019· article· en· W2989764035 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTransgender Health · 2019
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsVernon Jubilee HospitalUniversity of OttawaUniversity of Toronto
Fundersnot available
KeywordsTransgenderTerminologyTransgender PersonMedicineHealth careMEDLINEEnglish languagePathologyPsychologyLinguisticsPolitical science

Abstract

fetched live from OpenAlex

Abstract Background: The use of inclusive terminology in health records continues to be a challenge for transgender, gender-diverse, and nonbinary peoples. When patients access electronic health records, laboratory results, including pathology reports, are among the most frequently viewed items. There has been limited discussion of transgender care within laboratory medicine, despite its role in providing written pathology reports after gender-affirming surgery. Proposal: This group proposes inclusive diagnostic terminology for pathology reporting and puts forward recommendations for procedural descriptions in the pathology report. Finally, we highlight pathological information that should be included in a report that has future cancer screening or diagnostic consequences.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.094
GPT teacher head0.416
Teacher spread0.322 · 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