Use of Magnetic Resonance Imaging to Measure Facial Soft Tissue Depth
Bibliographic record
Abstract
OBJECTIVE: To investigate the feasibility of using magnetic resonance imaging to estimate facial tissue depth at standard anthropological facial landmarks. DESIGN: Standard facial landmarks were marked with magnetic resonance imaging opaque markers on 10 normal subjects. Three observers estimated facial tissue depth at these landmarks on up to three separate occasions, and comparisons were made among the observers. SETTING: The study was conducted with volunteers at the University of Alberta Biomechanical Engineering unit. PARTICIPANTS: The volunteers were healthy individuals of both sexes between the ages of 18 and 30 years. MAIN OUTCOME MEASURES: The technical error of measurement among observers was used as the main indicator of precision of measurement. RESULTS: Measurements of tissue depth showed tolerable technical error of measurement and were precisely measured within and among observers. CONCLUSIONS: Magnetic resonance images can be used to estimate tissue depth in human faces with precision.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".