Experimental Peri‐Implantitis around Different Types of Implants – A Clinical and Radiographic Study in Dogs
Bibliographic record
Abstract
BACKGROUND: The influence of the implant micro and macrostructure on peri-implantitis is not fully understood. PURPOSE: To determine the effect of ligature-induced peri-implantitis on three commercially available implant types. MATERIALS AND METHODS: Five beagle dogs were used. Two months following tooth extraction, three different implant types (BIOMET 3i T3, BIOMET 3i, Palm Beach Gardens, FL, USA; Straumann Bone Level, Straumann GmbH, Basel, Switzerland; Nobel Replace Tapered, Nobel Biocare, Gothenburg, Sweden) were placed in a randomized fashion in each hemi-mandible. Peri-implantitis was initiated by ligature placement and soft diet. Ligatures were added every 2 weeks for a total of four ligature advancements. After 2 weeks, the ligatures were removed, oral hygiene measures initiated for 3 weeks, and clinical (probing depth, mucosal recession, bleeding on probing), intrasurgical (intrasurgical defect depth, intrasurgical defect width), and radiographic (radiographic bone level) parameters assessed. RESULTS: Nobel Replace Tapered implants showed significantly higher intrasurgical defect depth, intrasurgical defect width, probing depths, and radiographic bone level when compared to BIOMET 3i T3 or Straumann Bone Level implants. Straumann Bone Level implants showed largely similar clinical outcomes to BIOMET 3i T3. No significant differences between the groups were observed for mean mucosal recession. CONCLUSION: In an experimental peri-implantitis model, Nobel Replace Tapered implants are associated with pronounced tissue loss.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".