Validated Assessment Scale for Neck Volume
Bibliographic record
Abstract
BACKGROUND: Sagging of the neck aesthetic area is an important indicator of age. The development of complex and globally accepted tools for proper assessment of the change in neck volume is an essential contribution to aesthetic research and the routine clinical setting. OBJECTIVE: To develop a grading scale for the objective assessment of the neck volume and to establish the reliability of this scale for clinical research and practice. MATERIALS AND METHODS: A 5-point rating scale was developed to assess neck volume objectively. Twelve experts rated frontal and lateral neck photographs of 50 subjects in two separate rating cycles using the neck volume scale. Responses of raters were analyzed to assess inter- and intrarater reliability. RESULTS: Interrater reliability for the neck volume scale was almost perfect, with intraclass correlation coefficients for the first and second rating cycles of 0.85 and 0.84, respectively. Intrarater reliability for the neck volume scale was high (0.90) and Pearson correlation coefficients ranged between 0.88 and 0.95 and were statistically significant. CONCLUSION: The neck volume scale demonstrates optimal reliability for clinical research and practice.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".