In-vitro analysis of stress dynamics in polyamide and metal acrylic distal extension removable partial dentures
Bibliographic record
Abstract
BACKGROUND: This study aimed to determine and compare the stresses transmitted by metal acrylic and polyamide removable partial dentures (RPDs) on free-end saddle areas. METHODS: Twenty metal acrylic and polyamide removable partial dentures were made. The stresses transmitted on the free end saddle area were determined and compared by using the strain gauge resistance method, in which sensors were installed in the epoxy resin cast. The load was applied on removable partial dentures with the underlying cast through the universal testing machine. Data was collected through the connected strain meter and computer. The analysis was done using ANSYS version 15, and the results were analyzed. RESULTS: The polyamide distal extension removable partial dentures transmit higher but even stresses on the free end saddle area compared to metal acrylic distal extension RPDs. The forces transmitted by polyamide distal extension base RPDs distribute an even load on the ridge, whereas metal acrylic distal extension base RPDs distribute an uneven load on the ridge. P value equal to and < 0.05 was considered significant, and our results showed insignificant statistical differences. CONCLUSION: Stress distribution in polyamide distal extension removable partial dentures is even compared to metal acrylic distal extension removable partial dentures. Even force distribution is less damaging to the bone and surrounding tissues.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".