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Record W3001962870 · doi:10.1542/peds.2019-1606

Long-term Puberty Suppression for a Nonbinary Teenager

2020· letter· en· W3001962870 on OpenAlexaff
Ken C. Pang, Lauren Notini, Rosalind McDougall, Lynn Gillam, Julian Savulescu, Dominic Wilkinson, David B. Clark, Johanna Olson-Kennedy, Michelle Telfer, John D. Lantos

Bibliographic record

VenuePEDIATRICS · 2020
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSexual Differentiation and Disorders
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGender dysphoriaTransgenderMedicineGender identityGender Identity DisorderTerm (time)Developmental psychologySocial psychologyPsychology

Abstract

fetched live from OpenAlex

Many transgender and gender-diverse people have a gender identity that does not conform to the binary categories of male or female; they have a nonbinary gender. Some nonbinary individuals are most comfortable with an androgynous gender expression. For those who have not yet fully progressed through puberty, puberty suppression with gonadotrophin-releasing hormone agonists can support an androgynous appearance. Although such treatment is shown to ameliorate the gender dysphoria and serious mental health issues commonly seen in transgender and gender-diverse young people, long-term use of puberty-suppressing medications carries physical health risks and raises various ethical dilemmas. In this Ethics Rounds, we analyze a case that raised issues about prolonged pubertal suppression for a patient with a nonbinary gender.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.269
Teacher spread0.250 · 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 designCase report
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

Citations16
Published2020
Admission routes1
Has abstractyes

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Same venuePEDIATRICSSame topicSexual Differentiation and DisordersFrench-language works237,207