Microcomputed Tomographic Analysis of the Alveolar Ridge Alteration around Extraction Sites with and without Immediate Implants Placement: In Vivo Study
Bibliographic record
Abstract
BACKGROUND: The aim was to assess the alveolar ridge alteration around extraction sites with and without immediate implants according to extraction socket classification (ESC) using microcomputed tomography (micro-CT). MATERIAL AND METHODS: Ten beagle dogs (mean age and weight: 24 ± 0.83 months and 13.8 ± 0.49 kg, respectively) were randomly divided into three groups according to the ESC. In Group 1 (ESC-I), bilateral first and third premolars were extracted and replaced with immediate implants. In Group 2 (ESC-II), two adjacent premolars were extracted with one immediate implant placement in the mesial socket in the maxilla and in the distal socket in the mandible. In Group 3 (ESC-III), three adjacent teeth were extracted and an immediate implant was placed in the central socket. Primary closure was achieved using resorbable sutures. Buccal sites with dehiscence defects were excluded. After 4 months, subjects were sacrificed and alveolar ridge widths were measured at 1 mm interval in axial and sagittal views, using micro-CT in sites with and without immediate implants. RESULTS: In sites without immediate implant placement, alveolar ridge width was significantly higher in Group 1(6.1 ± 1.35mm) than Group 3 (4.14 ± 1.53 mm) (p <.05). In sites with immediate implant placement, the alveolar ridge width was higher among sites in Group 1 (6.4 ± 3.8 mm) than Group 2 (4.8 ± 0.46 mm) (p < .05) and Group 3 (5.02 ± 0.84 mm) (p <.05). Overall, between each corresponding group in both sites with and without immediate implant placement at 1 mm thickness, there was no significant difference in the alveolar ridge widths. CONCLUSION: With the exception of Group 1 (ESC-I), immediate implant placement did not prevent or minimize bone remodeling in extraction sites according to ESC.
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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 | 0.000 | 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".