μFEA successfully exhibits higher stresses and strains in microdamaged regions of whole vertebrae
Bibliographic record
Abstract
Micro-finite element (μFE) modeling has shown promise in evaluating the structural integrity of trabecular bone. Histologic microcrack analyses have been compared to μFE models of trabecular bone cores to demonstrate the potential of this technique. To date this has not been achieved in whole bone structures, and comparisons of histologic microcrack and μFE results have been limited due to challenges in alignment of 2D sections with 3D data sets. The goal of this study was to ascertain if image registration can facilitate determination of a relationship between stresses and strains generated from μFE models of whole vertebrae and histologically identified microdamage. μFE models of three whole vertebrae, stained sequentially with calcein and fuchsin, were generated with accurate integration of element sets representing the histologic sections based on volumetric image registration. Displacement boundary conditions were applied to the μFE models based on registration of loaded and unloaded μCT images. Histologically labeled damaged regions were found to have significantly higher von Mises stresses and principle strains in the μFE models, as compared to undamaged regions. This work provides a new robust method for generating and histologically validating μFE models of whole bones that can represent trabecular damage resulting from complex physiologic loading.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".