Microarchitecture of the penis bone (baculum) of a seal: A <scp>3D</scp> morphometric examination using synchrotron and laboratory micro‐computed tomography
Bibliographic record
Abstract
We examined the ultrastructure of the mammalian os penis at the high-resolution synchrotron level. Previously, bacular microanatomy had only been investigated histologically. We studied the baculum of the harp seal (Pagophilus groenlandicus), in which the baculum varies more in size and shape than does a mechanically constrained bone (humerus). We (1) investigated the microarchitecture of bacula and humeri from the same seal specimens, and (2) described changes in bone micro- and macro-morphology associated with age (n = 15, age range = 1-35 years) and bone type. We analyzed cross-sectional geometry non-destructively through laboratory micro-computed tomography. We suggest that the midshaft may resist axial compression while the proximal region may resist torsion, based on measurements of cross-sectional and cortical areas, perimeter, ratio of maximum and minimum moments of inertia, and polar moment of inertia. In addition, midshaft bacula may be less mechanosensitive than humeri, based on microstructural variables (e.g., volume, surface area, diameter associated with lacunae and cortical porosity) analyzed across age groupings. Our findings related to the microarchitecture of the pinniped baculum provide a basis for further studies on development, mechanical properties, functions, and adaptations in this and other pinniped species. Our use of a multi-modal imaging approach was minimally destructive for reproducible and accurate comparison of three-dimensional bone ultrastructure. Such methods, coupled with multidisciplinary analyses, enable diverse studies of bone biology, life history, and evolution using museum collections.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".