Peri-implant tissue alteration around tissue-level and bone-level implants in fresh extraction sockets: a histomorphometric study in dogs
Bibliographic record
Abstract
BACKGROUND: To compare tissue alteration in fresh extraction sockets between bone-level and tissue-level implants with different neck designs. METHODS: Bilateral premolars of 6 adult Labrador dogs were extracted, and 24 bone-level and tissue-level implants with two different neck designs were immediately placed. At the same time, buccal bony wall thickness in fresh extraction sockets was also recorded. The Straumann® Bone Level (BL) and Standard Plus (SP) implants were positioned at two insertion depths: 1mm below and flush with the alveolar crest. All animals were sacrificed 6 months after the implant placement. Undecalcified block sections were obtained for histological measurement. Vertical bone resorption and biological widths were documented. Statistical analysis consisted of two sample t-test and Wilcoxon sign-rank test. RESULTS: All implants were histologically osseointegrated. There was no significant difference between BL implants and SP implants in vertical bone resorption regardless of the insertion depths (P>0.05). Meanwhile, significant difference was found in lingual biological width between BL (3.16 mm) and SP (2.43 mm) implants when placed 1mm below the alveolar crest (P<0.05). CONCLUSIONS: Within the limits, it seemed that different implant neck designs had little effect on bone remodeling in fresh extraction sockets. However, longer biological width was found in bone-level implants.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".