Trabecular bone microstructure and mineral density in human residual ridge at various intervals over a long period after tooth extraction
Bibliographic record
Abstract
BACKGROUND: Long-term changes of trabecular microstructure in human tooth extraction socket have not been investigated. PURPOSE: To examine the trabecular microstructure of human residual ridges at various intervals following tooth extraction, and to determine whether bone remodeling activity can attain points of relative stability and when such points are reached. MATERIALS AND METHODS: Forty-four bone biopsy specimens were obtained from lower molar or premolar regions of residual ridges. Postextraction times ranged from 1.6 to 360 months. Samples were analyzed using micro-computed tomography and three-dimensional bone morphometry with histological analyses. Trabecular bone parameters were plotted against postextraction times, and a stepwise piecewise linear regression analysis was performed to determine at which points of time these parameters either increased or decreased. RESULTS: Using piecewise linear regression, "inflection points" were found in most trabecular bone parameters between 7 and 12 months postextraction. Among the residual ridge samples, woven trabecular structure became mature, consisting of thick lamellar trabeculae with sufficient bone density, under dynamic bone remodeling until the 7th to 12th month post-tooth extraction. After this period, the mature network structure remained stable with low remodeling activity. CONCLUSION: Bone remodeling of trabecular structure in human residual ridge after tooth extraction had a stabilization period.
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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 | 0.000 |
| 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".