Finite element study of dominant stimulus in regulating femur bone remodeling
Bibliographic record
Abstract
Based on the Wolff’s law, mechanical stimuli affect bone strength and therefore affect its bone mineral density (BMD) distribution. There are a number of mechanical stimuli, for example, von-Mises stress, tensile stress, compressive stress, and strain energy density (SED). It is not clear which is the dominant stimulus. The objective of this study was to determine the dominant stimulus that regulates femur BMD by iterative finite element simulations of Wolff’s law. Four finite element models of the same femur initially had the same uniform BMD and were affected by the same loading. In the iterative simulations, BMD in each model was ‘remodeled’ by one of the four stimuli. The results showed BMD distribution in the finite element model regulated by SED was closest to QCT measured BMD, followed by von-Mises stress, then tensile and compressive stress. It is thus concluded that SED was the dominant stimulus in regulating femur BMD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".