The influence of composite bone plates in Vancouver femur B1 fracture fixation after post-operative, and healed bone stages: A finite element study
Bibliographic record
Abstract
Conventional stainless steel or titanium plates are used for bone fracture fixation to provide support at fracture location. Plates with high elastic modulus reduce the transfer of compressive load at the fracture location (due to stress shielding), causing failure. The objective of the study is to find for composite bone plates with different types of fibers and varied fiber orientations for post-operative (PO) and healed bone (HB) conditions which can reduce the stress shielding. Femur fracture fixation was constructed with 12 holes narrow type with metal and composite bone plates. The fracture gap was constructed with soft bone region for post-operative (PO) condition and harder bone for healed bone (HB). Composite bone plates with different configurations (fiber directions) and types (thickness and width) were analyzed to study the stress distribution and movement in the fracture location. The models were analyzed and the stresses in plate and callus, movement and strain in axial and shear direction in both metal and composite bone plates were studied. The metal and composite plates (carbon fiber/epoxy, fiberglass/epoxy, and flax/epoxy) used for most common Vancouver type B1 fracture to observe the biomechanical behavior of different models in PO and HB condition. The FE simulation on different configurations and types of composite plates provide in-depth idea about choosing the suitable composite bone plate. There are variations in behavior for varying types and configurations, but the performance of most of the plates are either better or similar to that of metal plate, except the plates with higher width.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".