Tridimensional assessment of the dental follicle dimensions of impacted mandibular third molars using cone-beam CT
Bibliographic record
Abstract
Background: The present study was performed to compare follicle dimensions of impacted mandibular third molar (IMTM) with different impaction angulations using cone beam computed tomography (CBCT).Material and Methods: Forty-nine individuals with IMTM (24 male, 25 female) were selected.Their age range was 25-55 years.The sample was divided into three IMTM groups either vertical (n=16), mesioangular (n=18) or horizontal (n=15) position based on Winter's classification (the angle between the longitudinal axis of the second and third molars).Follicular spaces (FS) from available CBCT imaging were measured from the midpoint of the teeth's crown in several dimensions (mesial, distal, occlusal, apical, vestibular and lingual) in axial, sagittal and coronal planes.An ANOVA, T-student, Kruskal-Wallis and Mann-Whitney U tests were used.Results: A comparison of the mesial FS for all groups revealed significant differences (p<0.001).Significant difference was also found for vestibular FS between the vertical and mesioangular IMTM groups (p=0.04).Buccolingual FS for all groups revealed no significant differences (p=0.074),whereas significant difference was found for the vertical and horizontal IMTM groups (p=0.02).No significant statistical differences were found for occlusal (p=0.54),apical (p=0.06), and lingual (p=0.64)FS.Conclusions: In this sample IMTM follicles have different dimensions according to their degree of angulation.Mesioagulated and horizontally positioned IMTMs seems to consistently have some increased FS dimensions (mesial and vestibular aspects).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".