Effect of mismatching abutments on implants with wider platforms – an experimental study in dogs
Bibliographic record
Abstract
AIM: To evaluate the effect of mismatching abutments on implants with a wider platform on the peri-implant hard tissue remodeling and the soft tissue dimensions. MATERIAL AND METHODS: Mandibular premolars and first molars of six Labrador dogs were extracted bilaterally. After 3 months of healing, one tapered implant was installed on each side of the mandibular molar region with the implant shoulder placed at the level of the buccal alveolar bony crest. On the right side of the mandible, an abutment of reduced diameter in relation to the platform of the implant was used, creating a mismatch of 0.85 mm (test), whereas an abutment of the same diameter of the implant platform was affixed in the left side of the mandible (control). The flaps were sutured to allow a non-submerged healing. After 4 months, the animals were sacrificed and ground sections were obtained for histometric assessment. RESULTS: All implants were completely osseo-integrated. Bone levels were superior at the test than at the control sites. However, statistically significant differences were found only at the buccal and proximal aspects. The soft tissue vertical dimension was higher at the control compared with the test sites. However, statistically significant differences were demonstrated only at the buccal aspects. CONCLUSIONS: A mismatch of 0.85 mm between the implant and the abutment yielded more coronal levels of bone-to-implant contact and a reduced height of the peri-implant soft tissue (biologic width), especially at the buccal aspect, if the implant shoulder was placed flush with the level of the buccal alveolar bony crest.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".