What Surgeons Need to Know About Gender Confirmation Surgery When Providing Care for Transgender Individuals
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.
Bibliographic record
Abstract
IMPORTANCE: In 2014, the US Department of Health and Human Services decided that its 1981 exclusion of transsexual surgical treatments from Medicare coverage was based on outdated, incomplete, and biased science and did not reflect current evidence or standards of care, and the exclusion was therefore lifted. As a direct result of this decision, surgeons nationwide are seeing an increase in consultations for surgical therapy to help transgender and gender-nonconforming individuals. Although some clinicians may have the technical training for such surgical procedures, in many cases, they may not have a full understanding of the complex and comprehensive care required to provide optimal health care for transgender individuals. OBSERVATIONS: Gender confirmation surgery is a developing field in the United States and other areas of the world. The World Professional Association for Transgender Health started a global education initiative intended to provide surgeons and other health care professionals with the necessary background knowledge to understand and treat this patient population. This article provides an overview of best practices as set forth in the seventh edition of the Standards of Care for the Health of Transsexual, Transgender, and Gender Nonconforming People by the World Professional Association for Transgender Health, including mental health, endocrinology, and surgery for trans women and trans men. CONCLUSIONS AND RELEVANCE: Experts in each aspect of transgender health have summarized the content of the global education initiative in this article. It provides valuable information to surgeons of all disciplines and other health care professionals to help guide the treatment and management of transgender individuals.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it