The Americleft Project
Bibliographic record
Abstract
BACKGROUND: The burden of care for children with cleft lip and palate extends beyond primary repair. Children may undergo multiple secondary surgeries to improve appearance or speech. The purpose of this study was to compare the use of secondary surgery between cleft centers. METHODS: This retrospective cohort study included 130 children with complete unilateral cleft lip and palate treated consecutively at 4 cleft centers in North America. Data were collected on all lip, palate, and nasal surgeries. Nasolabial appearance was rated by a panel of judges using the Asher-McDade scale. Risk of secondary surgery was compared between centers using the log-rank test, and hazard ratios estimated with a Cox proportional hazards model. RESULTS: Median follow-up was 18 years (interquartile range, 15-19). There were significant differences among centers in the risks of secondary lip surgery (P < 0.001) and secondary rhinoplasty (P < 0.001). The cumulative risk of secondary lip surgery by 10 years of age ranged from 5% to 60% among centers. The cumulative risk of secondary rhinoplasty by 20 years of age ranged from 47% to 79% among centers. No significant differences in nasolabial appearance were found between children who underwent secondary lip or nasal surgery and children who underwent only primary surgery (P > 0.10). CONCLUSIONS: Although some cleft centers were significantly more likely to perform secondary surgery, the use of secondary surgery did not achieve significantly better nasolabial appearance than what was achieved by children who underwent only primary surgery.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.309 | 0.096 |
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".