Morphometric evaluation of the early stages of healing at cortical and marrow compartments at titanium implants: an experimental study in the dog
Bibliographic record
Abstract
OBJECTIVE: To study the early sequential stages of tissue composition in the cortical and marrow compartments of the alveolar bone crest at implants with a moderately rough surface. MATERIALS AND METHODS: Three month after tooth extraction in 12 Labrador dogs, full-thickness flaps were elevated in the edentulous region of the right side of the mandible and one implant was installed. The flaps were sutured to allow a fully submerged healing. The timing of the installations in the left side of the mandible and of sacrifices were scheduled in such a way to obtained biopsies representing the healing after 5, 10, 20, and 30 days. Ground sections (n = 6 per each healing period) were prepared, and the percentages of osteoid/new bone, old bone, new soft tissues (provisional matrix and primitive marrow), mature bone marrow, vessels, and other tissues (bone debris/particles and clot) were evaluated laterally to the implant surface up to a distance of about 0.4 mm from it. RESULTS: Osteoid/new bone was found after 5 days at percentages of 10.8 ± 4.3% at the marrow and 0.6 ± 0.6% at the cortical compartments. After 30 days, these percentages increased up to 56.4 ± 4.0% and 23.3 ± 6.1%, respectively. Old parent bone was resorbed between 5 and 30 days from 28.7 ± 10.9% to 14.9 ± 3.4% at the marrow (~48% of resorption) and from 81.2 ± 9.4% to 67.6 ± 5.6% at the cortical (~17% of resorption) compartments. All differences were statistically significant. CONCLUSION: Bone apposition to an implant surface followed a significantly different pattern in the compact and the marrow compartments around the implants. While in the compact compartments, bone apposition had to develop through the BMUs following resorption, it developed in very dense layers through an early apposition in the marrow compartments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".