Spatial analysis of condyle position according to sagittal skeletal relationship, assessed by cone beam computed tomography
Bibliographic record
Abstract
BACKGROUND: The study aims to compare the condylar position in patients with different anteroposterior sagittal skeletal relationships through a cone beam computed generated tomography (CBCT) imaging generated space analysis. METHODS: This was a retrospective study of clinically justified, previously taken CBCT images of 45 subjects. Based on a proper sample calculation, three groups of 15 CBCT images each were made according to their ANB angle and facial pattern: class I (normo facial pattern) and class II and III (long facial pattern). The CBCT images were of adult patients between 18 and 35 years old, with full permanent dentition at maximum occlusal intercuspidation. Anatomical references previously used by Ricketts for the condyle position inside the glenoid fossae were measured digitally through the EzImplant software. Analysis of variance, Tukey's, Kruskal-Wallis, and Mann-Whitney U statistical tests were used. RESULTS: The upper distance of the condyle to the glenoid fossa was smaller in the class II and class III compared with the class I group. The anterior distance of the condyle to the articular eminence showed significant differences when comparing the class I with the class II and class III groups. No statistically significant difference was noted in the posterior condylar distance between the groups. The angle of the eminence showed differences between the three groups, while the eminence height showed significant difference when comparing the class I with class III group. CONCLUSIONS: Spatial differences existed for the condylar position in relation to the glenoid fossa for skeletal class I, class II, and class III, but these spatial differences may not be clinically relevant.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".