Tooth and root size as determined from 0.25- and 0.30-mm voxel size cone-beam CT imaging when contrasted to micro-CT scans (0.06 mm): An ex vivo study
Bibliographic record
Abstract
Objective: To quantify tooth volume differences from extracted teeth when using three different three-dimensional (3D) computed tomography (CT)-based imaging modalities. Design: Ex vivo study. Setting: Laboratory and clinics of the University of Alberta. Methods: Cone-beam CT (CBCT) of 12 extracted teeth were scanned using 0.25- and 0.30-mm voxel size from CBCT and a 0.06-mm voxel size from micro-CT (reference standard). 3D reconstructions for each tooth from each imaging modality were made through the software ITK-SNAP®. The mean volume differences between each pair of scanning modalities were calculated and then compared and analysed through a repeated measures ANOVA. Results: The average overestimations of the teeth volume were 15.2% for the high-resolution CBCT and 28.1% for the low-resolution CBCT compared to micro-CT measurements. The differences in absolute volume were 81.6 mm3 and 152.8 mm3, respectively. All differences were statistically significant ( P < 0.05). Conclusions: Orthodontists and researchers who assess root resorption through CBCT imaging should be aware that the depicted volumes may likely be overestimating tooth volume and camouflaging real root volumetric treatment 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".