The GLAND-IQ Technique for Surgical Correction of Moderate to Severe Gynecomastia
Bibliographic record
Abstract
Surgical correction of gynecomastia currently ranks in the top five cosmetic procedures performed in men in the United States. Although removal of excess gland is relatively straightforward, the combination of glandular/fatty excess, significant skin redundancy, nipple ptosis, and nipple-areolar complex hypertrophy poses a significant challenge in the male patient desiring inconspicuous scars. The latter renders any form of skin and nipple reduction/elevation using traditional mastopexy patterns or breast amputation with free nipple grafting less favorable due to the surgical stigmata and scars produced with these techniques. To that end, we present our experience treating cases of moderate to severe gynecomastia involving significant skin excess (defined as Simon grade IIb and III) with a technique focused on avoiding visible extra-areolar scars, called the glandular excision, liposuction-assisted, areolar mastopexy for nipple repositioning and skin reduction with internal quilting sutures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".