3D visualization and quantification of rat cortical bone porosity using a desktop micro‐CT system: a case study in the tibia
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Bibliographic record
Abstract
Although micro-computed tomography (micro-CT) has become the gold standard for assessing the 3D structure of trabecular bone, its extension to cortical bone microstructure has been relatively limited. Desktop micro-CT has been employed to assess cortical bone porosity of humans, whereas that of smaller animals, such as mice and rats, has thus far only been imaged using synchrotron-based micro-CT. The goal of this study was to determine if it is possible to visualize and quantify rat cortical porosity using desktop micro-CT. Tibiae (n = 10) from 30-week-old female Sprague-Dawley rats were imaged with micro-CT (3 μm nominal resolution) and sequential ground sections were then prepared. Bland-Altman plots were constructed to compare per cent porosity and mean canal diameter from micro-CT (3D) versus histology (2D). The mean difference or bias (histology-micro-CT; ±95% confidence interval) for per cent porosity was found to be -0.15% (±2.57%), which was not significantly different from zero (P= 0.720). Canal diameter had a bias (±95% confidence interval) of -5.73 μm (±4.02 μm) which was found to be significantly different from zero (P < 0.001). The results indicated that cortical porosity in rat bone can indeed be visualized by desktop micro-CT. Quantitative assessment of per cent porosity provided unbiased results, whereas direct analysis of mean canal diameter was overestimated by micro-CT. Thus, although higher resolution, such as that available from synchrotron micro-CT, may ultimately be required for precise geometric measurements, desktop micro-CT--which is far more accessible--is capable of yielding comparable measures of porosity and holds great promise for assessment of the 3D arrangement of cortical porosity in the rat.
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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 | 0.003 | 0.000 |
| 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 | 0.000 | 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 it