Quantification of Osteon Morphology Using Geometric Histomorphometrics
Bibliographic record
Abstract
Many histological methods in forensic anthropology utilize combinations of traditional histomorphometric parameters which may not accurately describe the morphology of microstructural features. Here, we report the novel application of a geometric morphometric method suitable when considering structures without anatomically homologous landmarks for the quantification of complete secondary osteon size and morphology. The method is tested for its suitability in the measurement of intact secondary osteons using osteons digitized from transverse femoral diaphyseal sections prepared from two human individuals. The results of methodological testing demonstrate the efficacy of the technique when applied to intact secondary osteons. In providing accurate characterization of micromorphology within the robust mathematical framework of geometric morphometrics, this method may surpass traditional histomorphometric variables currently employed in forensic research and practice. A preliminary study of the intersectional histomorphometric variation within the femoral diaphysis is made using this geometric histomorphometric method to demonstrate its potential.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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 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".