Evaluation of root length following treatment with clear aligners and two different fixed orthodontic appliances. A pilot study
Bibliographic record
Abstract
OBJECTIVES: The purpose of this pilot study was to evaluate the root lengths of upper incisors as an indication of the degree of orthodontically-induced apical root resorption following treatment with Smart Track® aligners and compare it with two different fixed orthodontic appliances – regular and Damon brackets – using cone-beam computerized tomography (CBCT). MATERIALS AND METHODS: The sample comprised 33 patients with class I malocclusion and 4–6 mm crowding divided in 3 groups; Group I: 11 patients treated with Smart Track® aligners, group II: 11 patients treated with Damon brackets, and group III: 11 patients with regular brackets. Maxillary incisors teeth lengths were assessed using Dolphin imaging software before and after treatment. All data were analyzed using analysis of variance and t-test. RESULTS: All groups showed statistically significant root resorption, 0–1.4 mm for clear aligners, 0.1–2.3 mm for Damon, and 0–2.5 mm for regular brackets group. However, cases treated with fixed appliance in general showed significantly higher resorption than those treated with Smart Track® aligners (P < 0.05). CONCLUSION: Orthodontically-induced root resorption, as evaluated by root length, is an inevitable drawback with different orthodontic techniques. However, the use of Smart Track® aligners showed less root resorption relative to regular fixed appliances.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".