Comparison of alveolar bone thickness and height after slow expansion using quad-helix or clear aligners
Bibliographic record
Abstract
Objective: The study was conducted to investigate the thickness and height of the alveolar bone of individual teeth after slow maxillary expansion (SME) with quad helix or clear aligner appliances and hypothesized that there is no difference in buccal alveolar bone thickness or heights in patients treated by either quad helix or clear aligners. Material and Methods: This is a retrospective study; the records of 22 patients treated between December 2019 to April 2020 by dental arch expansion using either clear aligners or quad helix appliances were retrieved and studied. The results obtained through cone beam computed tomography (CBCTs) before and immediately after maxillary expansion (2 + 1 mm per side) were analyzed (11 in the Quad Helix group and 11 in the clear aligner). The data collected was analyzed using linear and angular measurements obtained through On-demand 3D App software. Furthermore, Statistical Package for Social Sciences (SPSS) version 25.0 was used to present the findings by mean and standard deviations, and Scheffe's test was applied for comparing forces. Results: The results showed that the mean age of patients in the clear aligner group and Quad Helix was 16.27 ± 0.56 years and 15.5 ± 1.53 years, respectively. There was no difference in buccal alveolar bone thickness or heights in patients treated by either quad helix or clear aligners. This is due to the findings that suggest that there was a decrease in bone height and bone width when treated with a quad helix as compared to clear alignment. Conclusion: It can be concluded that the quad helix SME treatment affects alveolar bone integrity; therefore, clear aligners might be better for treating patients than the quad helix.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".