The Ideal Nasolabial Angle in Rhinoplasty
Bibliographic record
Abstract
BACKGROUND: In aesthetic rhinoplasty, the described ideal nasolabial angle ranges from 90 to 120 degrees, with variable anthropologic differences. The authors sought to verify the most aesthetic nasolabial angle as specifically perceived by a random prospective sample of the general population and determine whether age, sex, race, and education were independent associated predictors. METHODS: The authors prospectively recruited 98 random volunteers from the general population. They were asked to rank three different nasolabial angles for the female nose (100, 105, and 110 degrees) and the male nose (90, 100, and 105 degrees) as "most," "moderately," and "least aesthetic." Demographic data were used to determine correlations between aesthetic preferences. Pearson chi-square test and t test were used to determine statistical significance RESULTS: The most aesthetic female nasolabial angle was 104.9±4.0 degrees. The most aesthetic male nasolabial angle was 97.0±6.3 degrees. Male subjects, younger volunteers, Native Americans, and African Americans preferred more acute male nasolabial angles (90 degrees). Female subjects, volunteers older than 50 years, college graduates, those with a previous rhinoplasty, and Caucasian and Asian subjects preferred more obtuse male nasolabial angles. CONCLUSIONS: In the authors' sample of the general population, the ideal and most aesthetic nasolabial angle ranged from 100.9 to 108.9 degrees in the female nose and 90.7 to 103.3 degrees in the male nose. Age, sex, race, education, and having undergone a previous rhinoplasty were predictors of differences in the ideal male nasolabial angle but did not change preference of the female nasolabial angle.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".