Accuracy of Bolton analysis measured in laser scanned digital models compared with plaster models (gold standard) and cone-beam computer tomography images
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to compare the accuracy of Bolton analysis obtained from digital models scanned with the Ortho Insight three-dimensional (3D) laser scanner system to those obtained from cone-beam computed tomography (CBCT) images and traditional plaster models. METHODS: CBCT scans and plaster models were obtained from 50 patients. Plaster models were scanned using the Ortho Insight 3D laser scanner; Bolton ratios were calculated with its software. CBCT scans were imported and analyzed using AVIZO software. Plaster models were measured with a digital caliper. Data were analyzed with descriptive statistics and the intraclass correlation coefficient (ICC). RESULTS: Anterior and overall Bolton ratios obtained by the three different modalities exhibited excellent agreement (> 0.970). The mean differences between the scanned digital models and physical models and between the CBCT images and scanned digital models for overall Bolton ratios were 0.41 ± 0.305% and 0.45 ± 0.456%, respectively; for anterior Bolton ratios, 0.59 ± 0.520% and 1.01 ± 0.780%, respectively. ICC results showed that intraexaminer error reliability was generally excellent (> 0.858 for all three diagnostic modalities), with < 1.45% discrepancy in the Bolton analysis. CONCLUSIONS: Laser scanned digital models are highly accurate compared to physical models and CBCT scans for assessing the spatial relationships of dental arches for orthodontic diagnosis.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".