The ‘Bikini Lip Reduction’: A Detailed Approach to Hypertrophic Lips
Bibliographic record
Abstract
Excessively large lips represent an occasional but significant challenge in aesthetic surgery. Previously described techniques focus largely on the simple excision of a strip of tissue to reduce the lips, without specific attention to the resultant lip contour or to the volume relationship between the lips. The present paper describes a new technique for lip reduction, called the 'bikini lip reduction'. This technique not only reduces the volume of the lips, but also restores an attractive labial contour, as well as an ideal volume relationship between the upper and lower lips. Because it is based on aesthetic analysis, this technique consistently yields both smaller and more aesthetically appealing lips. Simply stated, the bikini lip reduction consists of excision of a 'bikini top' (two cups and a middle strap) from the upper lip and a 'bikini bottom' (a triangle) from the lower lip. The aesthetic results and the patient satisfaction achieved through the bikini lip reduction technique have been very satisfactory.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".