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Record W2996780882 · doi:10.1016/j.jsxm.2019.11.019

016 Establishing a Multidisciplinary, Academic Program in Penile Inversion Vaginoplasty

2020· article· en· W2996780882 on OpenAlexaffabout
Yonah Krakowsky, Alexandra Millman, Mitchell G. Goldenberg, Ethan D. Grober

Bibliographic record

VenueThe Journal of Sexual Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicFemale Genital Mutilation/Cutting Issues
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMultidisciplinary approachPsychosocialMedicineVaginoplastyJurisdictionMultidisciplinary teamContinuum of carePopulationGeneral surgeryNursingSurgeryPolitical scienceHealth carePsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

Individuals seeking penile inversion vaginoplasty (PIV) in Canada receive government support to obtain surgery in the Canadian province of Quebec, the United States, or overseas due to poor local access throughout the country. Travelling for surgical care is associated with poorer outcomes and a significant psychosocial burden. In 2019 the first model of a publically funded, academic, multidisciplinary trans surgical program was established to offer this surgery to the over 800 individuals waiting for PIV in the Canadian province of Ontario (population 14.5 million). This program serves a paradigm for the establishment of future trans surgical programs in jurisdictions with poor access. To describe the processes involved in establishing a multidisciplinary, academic program in PIV in a large jurisdiction with no prior access to this surgery. The additional resources, training and partnerships necessary in the establishment of a new PIV program are described and initial outcomes of the first three cases are reported.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.064
GPT teacher head0.350
Teacher spread0.286 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes2
Has abstractyes

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