Scaling VOI size in 3D μCT studies of trabecular bone: A test of the over‐sampling hypothesis
Bibliographic record
Abstract
For comparative 3D microCT studies of trabecular bone, the use of a volume of interest (VOI) scaled to body size may avoid over-sampling the trabecular mass in smaller versus larger-bodied taxa and comparison of regions that are not functionally homologous (Fajardo and Müller: Am J Phys Anthropol 115 (2001) 327-336), though the influence on quantitative analyses using scaled versus nonscaled VOIs remains poorly characterized. We compare trabecular architectural properties reflecting mass, organization, and orientation from three volumes of interest (large, scaled, and small) obtained from the distal first metacarpal in a sample of Homo (n = 10) and Pan (n = 12). We test the null hypotheses that neither absolute VOI size, nor scaling of the VOI to metacarpal size as a proxy for body size, biases intraspecific analyses nor impacts the detection of interspecific differences. These hypotheses were only partially supported. While certain properties (e.g., bone volume fraction or trabecular thickness) were not affected by varying VOI size within taxa, others were significantly impacted (e.g., intersection surface, connectivity, and structure). In comparing large versus scaled VOIs, we found that the large VOI inflated the number and/or magnitude of significant differences between Homo and Pan. In summary, our results support the use of scaled VOIs in studies of trabecular architecture.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| 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 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".