Commentary on: Labia Minora, Labia Majora, and Clitoral Hood Alteration: Experience-Based Recommendations
Bibliographic record
Abstract
It is with great pleasure that we discuss “Labia Minora, Labia Majora, and Clitoral Hood Alteration: Experience-Based Recommendations,” by Dr John G. Hunter.1 In this article, Dr Hunter provides pragmatic information on performing labia minora, clitoral hood, and labia majora surgery based on his observations and experience performing these procedures. Although more and more articles are being published covering topics in female cosmetic genital surgery, most focus on specific techniques or outcomes related to safety.2-5 In this article, Dr Hunter dives deeper into the subtleties of technique selection based on patient characteristics—the finesse of aesthetic plastic surgery. Dr Hunter outlines significant and subtle differences between the three most commonly performed approaches for labiaplasty: edge excision, wedge excision, and central excision/deepithelialization, and these are summarized in Table 1. He underscores the importance of addressing clitoral hood redundancy (if present) at the time of labiaplasty to avoid creating a disproportionate and unnatural-appearing …
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".