Repair of Bilateral Complete Cleft Lip: Intraoperative Nasolabial Anthropometry
Bibliographic record
Abstract
Synchronous repair of bilateral complete cleft lip and nasal deformity requires conception of three-dimensional form and fourth-dimensional changes with growth, as distorted by the malformation. The aim is to obviate typical postoperative nasolabial stigmata. The strategy is to construct fast-growing features on a smaller scale and slow-growing features on a normal or slightly larger scale. In this study, intraoperative alterations in nasolabial dimensions were documented by anthropometry in 46 consecutive infants with bilateral complete cleft lip. These values were averaged and compared with measures from normal Caucasian infants at ages 0 to 5 months and 6 to 12 months. Nasal height (n-sn) and nasal width (al-al), both fast-growing features, were set smaller (88 percent and 96 percent, respectively) than those of age-matched normal infants. In contrast, the slow-growing features, nasal protrusion (sn-prn) and columellar length, were constructed longer than normal (130 percent and 167 percent, respectively). Because all labial features grow rapidly, they were made diminutive in this study, with the exception of central vermilion-mucosal height (median tubercle), which was purposively made full. These maneuvers resulted in a normal, average overall upper-lip height (sn-sto). Two technical refinements also are described: (1) construction of deepithelialized bands flanking the philtral flap to improve surface contour; and (2) positioning and fixation of the dislocated alar cartilages, performed entirely through superiomedial nostril rim incisions.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".