Effects of bone density alterations on strain patterns in the pelvis: Application of a finite element model
Bibliographic record
Abstract
Insufficiency fractures occur when physiological loads are applied to bone deficient in mechanical resistance. A better understanding of pelvic mechanics and the effect of bone density alterations could lead to improved diagnosis and treatment of insufficiency fractures. This study aimed to develop and validate a subject-specific three-dimensional (3D) finite element (FE) model of a pelvis, to analyse pelvic strains as a function of interior and cortical surface bone density, and to compare high strain regions with common insufficiency fracture sites. The FE model yielded strong agreement between experimental and model strains. By means of the response surface method, changes to cortical surface bone density using the FE model were found to have a 60 per cent greater influence compared with changes in interior bone density. A small interaction was also found to exist between surface and interior bone densities (< 3 per cent), and a non-linear effect of surface bone density on strain was observed. Areas with greater increases in average principal strains with reductions in density in the FE model corresponded to areas prone to insufficiency fracture. Owing to the influence of cortical surface bone density on strain, it may be considered a strong global (non-linear) indicator for insufficiency fracture risk.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".