Comparison of two three-dimensional cephalometric analysis computer software
Bibliographic record
Abstract
BACKGROUND: Three-dimensional cephalometric analyses are getting more attraction in orthodontics. The aim of this study was to compare two softwares to evaluate three-dimensional cephalometric analyses of orthodontic treatment outcomes. MATERIALS AND METHODS: Twenty cone beam computed tomography images were obtained using i-CAT(®) imaging system from patient's records as part of their regular orthodontic records. The images were analyzed using InVivoDental5.0 (Anatomage Inc.) and 3DCeph™ (University of Illinois at Chicago, Chicago, IL, USA) software. Before and after orthodontic treatments data were analyzed using t-test. RESULTS: Reliability test using interclass correlation coefficient was stronger for InVivoDental5.0 (0.83-0.98) compared with 3DCeph™ (0.51-0.90). Paired t-test comparison of the two softwares shows no statistical significant difference in the measurements made in the two softwares. CONCLUSIONS: InVivoDental5.0 measurements are more reproducible and user friendly when compared to 3DCeph™. No statistical difference between the two softwares in linear or angular measurements. 3DCeph™ is more time-consuming in performing three-dimensional analysis compared with InVivoDental5.0.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".