The biomechanical effect of changes in cancellous bone density on synthetic femur behaviour
Bibliographic record
Abstract
Biomechanical researchers increasingly use commercially available and experimentally validated synthetic femurs to mimic human femurs. However, the choice of cancellous bone density for these artificial femurs appears to be done arbitrarily. The aim of the work reported in this paper was to examine the effect of synthetic cancellous bone density on the mechanical behaviour of synthetic femurs. Thirty left, large, fourth-generation composite femurs were mounted onto an Instron material testing system. The femurs were divided evenly into five groups each containing six femurs, each group representing a different synthetic cancellous bone density: 0.08, 0.16, 0.24, 0.32, and 0.48 g/cm3. Femurs were tested non-destructively to obtain axial, lateral, and torsional stiffness, followed by destructive tests to measure axial failure load, displacement, and energy. Experimental results yielded the following ranges and the coefficient of determination for a linear regression (R2) with cancellous bone density: axial stiffness (range 2116.5-2530.6N/mm; R2 = 0.94), lateral stiffness (range 204.3-227.8N/mm; R2 = 0.08), torsional stiffness (range 259.9-281.5N/mm; R2 = 0.91), failure load (range 5527.6-11 109.3 N; R2 = 0.92), failure displacement (range 2.97-6.49 mm; R2 = 0.85), and failure energy (range 8.79-42.81 J; R2 = 0.91). These synthetic femurs showed no density effect on lateral stiffness and only a moderate influence on axial and torsional stiffness; however, there was a strong density effect on axial failure load, displacement, and energy. Because these synthetic femurs have previously been experimentally validated against human femurs, these trends may be generalized to the clinical situation. This is the first study in the literature to perform such an assessment.
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How this classification was reachedexpand
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".