Quantitative approach to identifying abnormal variation in the human face exemplified by a study of 278 individuals with five craniofacial syndromes
Bibliographic record
Abstract
We have two objectives in this study: to demonstrate the utility of two summary anthropometric measures for quantifying craniofacial variation and to explore some of their potential uses by physicians and clinical morphologists in general. The Craniofacial Variability Index (CVI) is a summary anthropometric measure of facial "harmony." The mean z-score, based on craniofacial anthropometry, is a measure of overall facial size. Both add an objective component to the assessment of individual facial variation and allow us to place the individual along a scale of continuous variation with predetermined limits of "normality" based on a reference or control series. Our results suggest that these summary measures coincide well with clinical assessments of abnormality in 278 individuals representing five distinct syndromes (Brachmann-de Lange, Prader-Willi, Rubinstein-Taybi, Smith-Magenis, and Sotos), each of which has an associated craniofacial component. Although craniofacial variation is continuous and the normal and syndromic populations overlap to varying degrees, the syndromic cases can be characterized in a variety of ways by using CVI as a measure of facial harmony and Mean-Z as an indicator of overall facial size. Thus, these two-objective measures offer a novel and efficient means of assessing craniofacial variation, whether they are used as tools in the clinical evaluation of subjects or as a means of exploring the nature of craniofacial variation within or between syndromes.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".