Influence on alveolar resorption of the buccal bony plate width in the edentulous ridge expansion (E.R.E.) – an experimental study in the dog
Bibliographic record
Abstract
OBJECTIVE: To compare the hard tissue changes at implants installed applying edentulous ridge expansion (E.R.E.) at sites with a buccal bony wall thickness of 1 or 2 mm. MATERIAL AND METHODS: In six Labrador dogs, the first and second maxillary incisors were extracted, and the buccal alveolar bony plates and septa were removed. After 3 months of healing, partial-thickness flaps were dissected, and the E.R.E. was applied bilaterally. Hence, an expansion of the buccal bony crest was obtained in both sides of the maxilla with a displacement of either a 1- or a 2-mm-wide buccal bony plate at the test and control sites, respectively. After 3 months of healing, biopsies were obtained for histological analyses. RESULTS: A buccal vertical resorption of the alveolar crest of 2.3 ± 0.8 and 2.1 ± 1.1 mm, and a coronal level of osseointegration at the buccal aspect of 2.7 ± 0.5 and 2.9 ± 0.9 mm were found at the test (1 mm) and control (2 mm) sites, respectively. The differences did not reach statistical significance. The mean values of the mineralized bone-to-implant contact (MBIC%) ranged from 62% to 73% at the buccal and lingual sites. No statistically significant differences were found. Horizontal volume gains of 1.8 and 1.1 mm were observed at the test and control sites, respectively, and the difference being statistically significant. CONCLUSIONS: Implants installed using the E.R.E. technique yielded a high degree of osseointegration. It is suggested that the displacement of buccal bony plates of 1 mm thickness is preferable compared with that of wider dimensions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".