Effects of Immediate and Delayed Loading on Peri‐Implant Trabecular Structures: A Cone Beam <scp>CT</scp> Evaluation
Bibliographic record
Abstract
PURPOSE: To develop a method for characterizing trabecular bone microarchitecture using cone beam computed tomography (CBCT) and to evaluate trabecular bone changes after rehabilitation using immediate versus delayed implant protocols. MATERIALS AND METHODS: Six mongrel dogs randomly received 27 titanium implants in the maxillary incisor or mandibular premolar areas, following one of four protocols: (1) normal extraction socket healing; (2) immediate implant placement and immediate loading; (3) delayed implant placement and delayed loading; (4) delayed implant placement and immediate loading. The animals were euthanized at 8 weeks, and block biopsies were scanned using high resolution CBCT. Standard bone structural variables were assessed in coronal, middle, and apical levels. RESULTS: Coronal and middle regions had more compact, more platelike, and thicker trabeculae. Protocols (2), (3), and (4) had significantly higher values (p < 0.001) than protocol (1) for bone surface density, bone surface volume ratio, and connectivity density, while significantly lower values (p < 0.001) were found for trabecular separation and fractal dimension. However, protocols (2), (3), and (4) did not show significantly different bone remodeling. CONCLUSIONS: Compared with normal extraction healing, the implant protocols have an improved bone structural integration. Results do not suggest a different bone remodeling pattern when a delayed versus an immediate implant protocol is used.
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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 | 0.001 |
| 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".