Validated Assessment Scales for the Mid Face
Bibliographic record
Abstract
BACKGROUND: The improvement of aesthetic treatment options for age-related mid face changes, such as volume loss, and the increase in patient expectations necessitates the development of more-complex and globally accepted assessment tools. OBJECTIVE: To develop three grading scales for objective assessment of the infraorbital hollow and upper and lower cheek fullness and to establish the reliability of these scales for clinical research and practice. METHODS AND MATERIALS: Three 5-point rating scales were developed to assess infraorbital hollow and upper and lower cheek fullness objectively. Twelve experts rated identical mid face photographs of 50 subjects in two separate rating cycles using the mid face scales. Test responses of raters were analyzed to assess intra- and interrater reliability. RESULTS: Interrater reliability was substantial for the infraorbital hollow, upper cheek fullness, and lower cheek fullness scales. Intrarater reliability was high for all three scales. Both of the cheek fullness scales yielded higher reliabilities when three rather than two views were used to assess the volume changes of the cheek. CONCLUSION: The mid face scales are reliable tools for valid and reproducible assessment of age-related mid face changes.
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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 | 0.015 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".