Surgical Accuracy of Maxillomandibular Clockwise Rotation Using Computer-Aided Surgical Planning in Skeletal Class III Patients
Bibliographic record
Abstract
This retrospective study aimed to evaluate the 3-dimensional (3D) surgical accuracy by comparing the virtual movements of computer-aided surgical planning (CASP) with the outcomes of actual surgery (AS) in class III patients treated with clockwise rotation of the maxillomandibular complex. Twenty adult patients with skeletal class III malocclusion were included, all of whom received bimaxillary surgery using CASP, including LeFort I and bilateral sagittal split ramus osteotomies. The AS was performed using 3D surgical splints printed based on the CASP. Cone-beam computed tomography (CBCT) scans were taken before surgery (T0) and 1 month after surgery (T1). The virtual movements predicted by the CASP (CASP-T0) and the outcomes of AS (T1-T0) on 3D landmark coordinates were compared using paired t test or Wilcoxon signed-rank test. The maxillary landmarks at AS showed errors ranging from 0.02 to 0.68 mm compared with CASP in terms of advancement, impaction, and transverse movements. The impaction of posterior nasal spine at AS was significantly smaller than predicted by CASP (3.47 versus 4.15 mm; P <0.05). The mandibular landmarks at AS showed errors ranging from 0.06 to 1.16 mm compared with CASP in posterior, superior, and lateral movements. There was significantly less superior movement of the distal segment in AS. However, there were no changes in the condylar position and lateral ramal inclinations in AS. Application of CASP can help clinicians achieve predictable and accurate surgical outcomes.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".