Performance parametric formulation of carbon fiber-reinforced composite locking bone implant plates based on finite-element analysis
Why this work is in the frame
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Bibliographic record
Abstract
The treatment of Giant Cell Tumor (GCT) in the distal radius poses challenges due to the intricate anatomical features of the bone. It often necessitates the use of long implant plates or the interconnection of multiple short plates after tumor excision. However, the deployment of metal plates may increase the risk of screw loosening and various complications. To address these challenges, this study proposes the adoption of carbon fiber-reinforced PEEK (CFRP) as the base material. As a unique strategy, performance parameters (PP) were developed to compare CFRP implant plates with a Ti-6Al-4V plate using the Finite-element Method. The focus was on four elements: the screw axial force, bone growth, callus formation, and bone resorption. The investigation into the screw axial force involved analyzing the internal force of the screw. The remaining parameters were evaluated using the stress, strain, or elastic energy induced in the bones. The findings showed that the second screw endured the largest screw axial force, measuring 10.16 N under a 90-degree 10-N loading at the translocated bone. The model without a callus exerted a significantly greater force on the screw than the model with a callus, leading to screw loosening in the early stage of treatment. The maximum PP, reached 1.62, was achieved with an angle-ply [456/−456] laminate, featuring a weighting fraction of 0.7 for bone growth and 0.1 for the other parameters. This study provides a generalized methodology for assessing the performances of CFRP implants and offers guidelines for future development in composite implant plate technology.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it