Association between intracortical microarchitecture and the compressive fatigue life of human bone: A pilot study
Bibliographic record
Abstract
Many mechanical properties of cortical bone are largely governed by the underlying microarchitecture; however, the influence of microarchitecture on the fatigue life of bone is poorly understood. Furthermore, imaging-based studies investigating intracortical microarchitecture may expose bone samples to large doses of radiation that may compromise fatigue resistance. The purpose of this pilot study was to 1) investigate the relationship between intracortical microarchitecture and the fatigue life of human bone in compression and 2) examine the effects of synchrotron irradiation on fatigue life measurements. Cortical samples were prepared from the femoral and tibial shafts of three cadaveric donors. A subset of samples was imaged using synchrotron X-ray microCT to quantify microarchitecture, including porosity, canal diameter, lacunar density, lacunar volume, and lacunar orientation. A second group of control samples was not imaged and used only for mechanical testing. Fatigue life was quantified by cyclically loading both groups in zero-compression until failure. Increased porosity and larger canal diameter were both logarithmically related to a shorter fatigue life, whereas lacunar density demonstrated a positive linear relationship with fatigue life (r2 = 45–73%, depending on measure). Irradiation from microCT scanning reduced fatigue life measurements by 91%, but relationships with microarchitecture measurements remained. Additional research is needed to support the findings of this pilot study and fully establish the relationship between intracortical microarchitecture and the compressive fatigue life of bone.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".