Influence of the Connector and Implant Design on the Implant–Tooth‐Connected Prostheses
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to evaluate stress transfer patterns between implant-tooth-connected prostheses comparing rigid and semirigid connectors and internal and external hexagon implants. MATERIALS AND METHODS: Two models were made of photoelastic resin PL-2, with an internal hexagon implant of 4.00 x 13 mm and another with an external hexagon implant of 4.00 x 13 mm. Three denture designs were fabricated for each implant model, incorporating one type of connection in each one to connect implants and teeth: 1) welded rigid connection; 2) semirigid connection; and 3) rigid connection with occlusal screw. The models were placed in the polariscope, and 100-N axial forces were applied on fixed points on the occlusal surface of the dentures. RESULTS: There was a trend toward less intensity in the stresses on the semirigid connection and solid rigid connection in the model with the external hexagon; among the three types of connections in the model with the internal hexagon implant, the semirigid connection was the most unfavorable one; in the tooth-implant association, it is preferable to use the external hexagon implant. CONCLUSIONS: The internal hexagon implant establishes a greater depth of hexagon retention and an increase in the level of denture stability in comparison with the implant with the external hexagon. However, this greater stability of the internal hexagon generated greater stresses in the abutment structures. Therefore, when this association is necessary, it is preferable to use the external hexagon implant.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".