Three-dimensional evaluation of the predictability of clear aligners in the treatment of maxillary transverse and anteroposterior tooth movements using cone beam computed tomography: A preliminary retrospective study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the predictability of clear aligner treatment in correcting maxillary transverse and anteroposterior movements using cone beam computed tomography (CBCT). METHODS: Thirty orthodontic patients who underwent orthodontic treatment using clear aligners were enrolled. Predicted tooth movements were obtained using digital orthodontic treatment planning software for clear aligners, while actual tooth movements were calculated by measuring the difference between pre- and post-treatment tooth positions using CBCT. Statistical analyses were done using the paired sample t -tests to compare the mean differences between predicted and actual movements at the crown and root levels. RESULTS: There were significant mean differences in the transverse dimension between the actual and predicted movements at the crown level for the first molars and first premolars and root level, 1.88 mm (±1.6), 0.64 mm (±1.7), 5.50 mm (±3.1), and 3.10 mm (±3.1), respectively ( P < 0.05). In contrast, no difference was seen in the canines at crown or root levels ( P > 0.05). There was a significant mean difference of 6.4 mm (±5.6) in the anteroposterior movements of incisors between actual and predicted measurements in the proclination group ( P < 0.05). In contrast, no difference was seen in the retroclination group (2.02 mm (±6.8)) ( P > 0.05). CONCLUSION: Orthodontic tooth movement using clear aligners showed that transverse movements at the canines are more predictable than at premolars and molars. Retroclination is more predictable than proclination; however, retrusive movements are less predictable than protrusive movements.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".