The Mini–Wise Pattern Nipple-Share Technique for Enhanced Nipple Reconstruction
Bibliographic record
Abstract
Nipple-areola complex reconstruction is a critical component of postmastectomy breast reconstruction, with a significant impact on patient satisfaction. Traditional techniques, such as flap-based methods and nipple grafting, can be limited by suboptimal long-term nipple projection, the lack of natural pigmentation, and the presence of surrounding scars. This article describes the mini-Wise pattern nipple-share technique, a modified surgical approach designed to address these challenges. Particularly suited for skin-sparing and areola-sparing mastectomies, this technique preserves native pigmentation and, for areola sparing, eliminates the need for postreconstruction tattooing. It avoids full-thickness incisions in hostile recipient milieus, including radiated skin and prepectoral alloplastic reconstructions. "Discarding nothing that could be useful," the mini-Wise pattern nipple-share technique not only results in an aesthetically pleasing donor site, but also maximizes available tissue by borrowing from traditional 3-dimensional concepts to create a sustainable projection of both the donor and recipient.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".