Bibliographic record
Abstract
The results of combining breast augmentation and mastopexy are less predictable than those associated with mastopexy or augmentation mammoplasty alone. A method of breast skin envelope reduction is presented that allows the surgeon performing mastopexy to preview the final breast shape before committing to skin resection. This method, first described in 1978, has proven to be technically versatile and reproducible, and applicable not only to moderate (second degree) and severe (third degree) ptosis but also to simultaneous breast augmentation and mastopexy. For the combined procedures, the practical strategy proposed is first the implant placement through a periareolar incision, and a vertical transglandular incision, usually submusculofascial; second, restoring the gland anatomy by closing the muscularis and the vertical transglandular incision; third, skin envelope adjustment using the Tailor-Tack maneuver to accurately assure the best position of the nipple-areolar complex on the breast mound; fourth, skin incision, de-epithelialization and undermining; and finally, closure combining the the Purse-String maneuver with the vertical incision.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.007 | 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".