Bone–implant contact at calcium phosphate‐coated and porous titanium oxide (TiUnite<sup>™</sup>)‐modified oral implants
Bibliographic record
Abstract
BACKGROUND: Calcium phosphate (CP)-coated implants are usually referred to as having osteoconductive properties, whereas titanium implants with a native oxide layer are considered less osteoconductive. Often smooth titanium oxides (TOs) are compared to relatively rough CP structures. The objective of this study was to evaluate osteoconduction by comparing bone-implant contact at a relatively smooth, highly crystalline CP coating with a structured, porous TO (TiUnite)-modified surface. MATERIAL AND METHODS: Ten adult Hound Labrador mongrel dogs were used. Four titanium implants (Nobel Biocare) with CP-coated (2) or TO-modified (2) surfaces were installed 12 weeks following mandibular premolar and molar teeth extraction. The implants were alternated within and between jaw quadrants in consecutive animals. Mucosal flaps were advanced and sutured leaving the implants in a submerged position. The animals were injected with fluorescent bone labels at 3 and 4 weeks postsurgery, and pre-euthanasia to monitor progress of bone formation. The animals were euthanized at 8 weeks postsurgery and block biopsies were prepared for histologic and histometric analysis. RESULTS: There were no remarkable differences in bone formation and apparent bone-implant contact comparing the TO-modified and CP-coated surfaces. However, the measured average bone-implant contact was 71% and 57% (P=0.027) for TO-modified and CP-coated implants, respectively. CONCLUSIONS: We conclude that the TO surface exhibits osteoconductive properties exceeding that of the CP surface. One or several of the chemical and physical properties of the TO surface may result in the remarkable bone formation along its surface. This study indicated that crystallinity and/or chemistry may be important.
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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 | 0.000 |
| 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".