Video-Imaging Assessment of Nasal Morphology in Individuals With Complete Unilateral Cleft Lip and Palate
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to develop a video-imaging mathematical method to assess nostril morphology. DESIGN: This retrospective study involved two age-matched groups: 28 subjects with complete unilateral cleft lip and palate (CUCLP) and 19 noncleft controls. Nose casts were reproducibly oriented in a jig such that the casts could be rotated about the coronal axis. Video images of the nostrils were captured and then analyzed for area, perimeter, centroid, principal axis, moments about the major and minor axes (I11, I22), anisometry, bulkiness, lateral offset, internostril angle, and rotational angle. RESULTS: All parameters identified nostril asymmetry in both groups. The results of the analyses using anisometry, I11, and I22 showed that, in both groups, one nostril was rounder and one was more elliptical. This asymmetry, however, differed between the two groups, and the difference was primarily based on the degree of ellipticity of the nostrils. Maximum dimension, perimeter, lateral offset, I11, and I22 were more asymmetric in the cleft group. In the control group, the right nostril was more elliptical and had a greater perimeter, and the left-side nostril had a greater bulkiness (enfolding). CONCLUSIONS: The method developed was validated for assessment of nasal morphology in cleft and noncleft samples. Nostril morphology was asymmetric in both groups but more asymmetric in the cleft group than the control group. The dominant influence of the cleft resulted in more elliptical noncleft nostrils and greater nostril shape asymmetry in the cleft group. The validated video-imaging method can now be used to assess the efficacy of treatment on nasal morphology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".