Surface Anatomy of the Face in Down's Syndrome: Anthropometric Proportion Indices in the Craniofacial Regions
Bibliographic record
Abstract
The objective of the study was to identify the proportions closest to normal and those indicating mild-to-moderate and severe degrees of disproportion. Eight proportion indices were analyzed in five craniofacial regions of 125 Down's syndrome patients, based on a total of 985 data points. More than two thirds of the patients fell within the normal range, although more than one quarter were abnormal (disproportionate). All statistical summaries were based on z-scores (adjusting for age and sex differences), converted into descriptive anthropometric categories to yield a simplified frequency distribution for each proportion index. Normal proportions were harmonious in 55.9% of patients. Disproportions were mild to moderate in 66.4%, severe in 33.6%. The highest frequency of harmony was found in the head (70.2%), the lowest in the orbits (40.8%). The highest percentage of mild-moderate disproportion was found in the face (79.3%). The highest percentage of severe disproportions was recorded in the intercanthal index of the orbits (44.7%) and the smallest frequency in the face (20.7%). In the five craniofacial regions among the normal proportions, harmonies were more frequent than disharmonies. Among the disproportions, the percentage of mild-moderate ones was greater than those of severe degree.
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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 | 0.001 | 0.001 |
| 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".