Assessment of craniovertebromandibular symmetry using cone-beam computed tomography: validation of a patented three-dimensional diagnostic method
Bibliographic record
Abstract
AIM. The aim of the study was to validate a patented three-dimensional method for assessing craniovertebromandibular symmetry using cone-beam computed tomography (CBCT) in patients with temporomandibular joint dysfunction (TMJD). MATERIALS AND METHODS. Ninety patients (54 females and 36 males), aged 19–60 years, diagnosed with temporomandibular joint dysfunction (TMJD) and exhibiting extraocclusal disorders, were included in the study. A standardized CBCT protocol (FOV ≥ 13 × 15 cm) including the cranial base and cervical vertebrae C 0 –C 2 was applied. Three-dimensional cephalometric analysis was performed in coronal, axial, and sagittal planes, measuring angular and linear parameters between cranial, mandibular, and cervical landmarks. Intra-class correlation coefficients (ICC) were calculated to determine reproducibility. Statistical analysis was conducted using paired t-tests, with significance set at p < 0.05. RESULTS. Asymmetry was observed in 100% of subjects, regardless of clinically symmetrical occlusion. The largest deviations were found in the Zy–Go angular measurement, reflecting predominant cranial-mandibular imbalance. Significant right–left differences were recorded across all reference lines (Zy–Go, Po–U6, C 0 –C 1 , C 1 –C 2 ) ( p < 0.01–0.001). Mean ICC values exceeded 0.90, confirming high methodological reliability. CONCLUSIONS. It was established that craniovertebromandibular asymmetry occurs in all patients with TMJD and identified extraocclusal disturbances. The developed CBCT-based protocol allows precise quantification of cranio-cervico-mandibular relationships, enhancing diagnostic accuracy and supporting individualized interdisciplinary management of occlusal and postural disturbances.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".