Three‐dimensional microcomputed tomography imaging of basic multicellular unit‐related resorption spaces in human cortical bone
Bibliographic record
Abstract
This study employed microcomputed tomography (micro-CT) as a novel means for visualizing the morphology and quantifying the range (length) of basic multicellular unit (BMU)-related resorption spaces in human cortical bone. We tested the hypotheses that the density and range of spaces vary with age and sex. The sample included 82 human (18-92 years) anterior femoral midshaft samples. The morphology of the spaces (n = 99) was varied, including unidirectional, bidirectional, branched, and even highly clustered forms. The density of resorption spaces was negatively correlated with age for the combined sexes and females, with Spearman's rho values of -0.355 (P < 0.001) and -0.522 (P = 0.002), respectively. The density of spaces did not differ significantly between the sexes (P = 0.735). Mean range +/- SD for the combined sexes, females, and males was 2,706 +/- 1,177, 2,681 +/- 1,247, and 2,718 +/- 1,150 microm, respectively. Numerical simulation of the effect of the 7,000 microm scan field of view suggested that the actual mean range of the spaces for the pooled sample was actually on the order of 3,770 microm. Range did not correlate significantly with age for the combined sexes (P = 0.587) or females (P = 0.345) and males (P = 0.896) considered separately and was not significantly different (P = 0.883) between the sexes. These results suggest that the range of BMUs is not affected by age. The age-dependent decrease in resorption space density for the females and pooled sexes was most likely a consequence of cortical rarefaction, leading to difficulty detecting resorption spaces with micro-CT, rather than a decrease in overall remodeling activity.
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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 | 0.001 | 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 | 0.000 |
| 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 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".