The platform switching concept revisited. An experimental study in dogs
Bibliographic record
Abstract
OBJECTIVE: To evaluate the influence of the configuration of the marginal aspect of implants placed immediately into extraction sockets on peri-implant hard tissue adaptation. MATERIAL AND METHODS: In 6 Labrador dogs, endodontic treatments of the mesial roots of 1 M1 were performed and the distal roots were removed. 2 P2 was extracted as well. Implants were immediately placed in the center of the distal alveoli. Cylindrical straight implants were installed in the right side of the mandible (Control), while, in the left side, implants with a reduced diameter in the coronal portion, yielding an indentation in the surface continuity (Test), were installed. Cover screws were affixed, and the flaps were sutured to allow non-submerged healing. After 4 months of healing, histological slides were obtained for assessments. RESULTS: A buccal resorption of 1.58 ± 1.28 and 1.90 ± 1.93 mm at the control and of 0.26 ± 0.90 and 0.14 ± 0.66 mm at the test sites was observed at the premolar and molar regions, respectively. The buccal coronal level of osseointegration was located apically to the margin of the smooth/rough surface border by 2.40 ± 0.90 and 3.70 ± 0.87 mm at the control sites and 1.19 ± 0.45 and 2.16 ± 0.96 mm at the test sites at the premolar and molar sites, respectively. All differences yielded statistical significance. CONCLUSIONS: The use of implants with a reduced diameter in their coronal aspect may contribute to preservation of the buccal bony crest in a more coronal level compared with conventional implants. Thus, the study confirmed the efficacy of the "platform switching" concept.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".