Stress Distribution Pattern in Zygomatic Implants Supporting Different Superstructure Materials
Bibliographic record
Abstract
The aim of this study was to assess and compare the stress-strain pattern of zygomatic dental implants supporting different superstructures using 3D finite element analysis (FEA). A model of a tridimensional edentulous maxilla with four dental implants was designed using the computer-aided design (CAD) software. Two standard and two zygomatic implants were positioned to support the U-shaped bar superstructure. In the computer-aided engineering (CAE) software, different materials have been simulated for the superstructure: cobalt-chrome (CoCr) alloy, titanium alloy (Ti), zirconia (Zr), carbon-fiber polymers (CF) and polyetheretherketone (PEEK). An axial load of 500 N was applied in the posterior regions near the zygomatic implants. Considering the mechanical response of the bone tissue, all superstructure materials resulted in homogeneous strain and thus could reconstruct the edentulous maxilla. However, with the aim to reduce the stress in the zygomatic implants and prosthetic screws, stiffer materials, such Zr, CoCr and Ti, appeared to be a preferable option.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".