Assessment of soft tissue facial asymmetry in medically normal and syndrome-affected individuals by analysis of landmarks and measurements
Bibliographic record
Abstract
We investigated soft tissue facial asymmetry in normal and syndrome-affected individuals ranging in age from 1 year to adulthood. The purposes of our study were to determine if facial asymmetry was greater in syndrome-affected individuals than in normal individuals and, if true, to distinguish those measurements that could be used in routine screening to identify the presence of syndromes in uncertain patients and, lastly, to investigate the causes of measurement asymmetry at the level of the landmarks. The last purpose was possible because we used a stereophotogrammetric method with which the three-dimensional (3D) landmark positions were obtained. In the statistically significantly different measurements, those from the right side were dominant, with one exception in each group, except normal males. In all groups the landmark analyses demonstrated the same trends, and while there was far less patterning in the 3D coordinates, these results were also consistent between the four groups. We compared the statistical findings of the 3D coordinates and measurements and found that there was no predictable relationship between significant findings in the landmarks and the measurements. In particular, we noted that statistical differences in measurements did not infer significant differences in the positions of the landmarks between the right and left sides of the face. Both the normal and syndrome-affected groups appeared to be equally canalized and similarly affected by developmental noise: When the bilateral measurement differences of each syndrome-affected subject were compared to the limits of normal asymmetry, less than 10% of the comparisons exceeded the norms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.002 | 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".