The vascular collar of the ilium— Three‐dimensional evaluation of the dominant nutrient foramen
Bibliographic record
Abstract
Nutrient arteries are the predominant blood supply to endochondral bones and are particularly important during the early stages of endochondral ossification and the active growth period. These nutrient vessels traverse the periosteal shell of a developing bone to invade the disintegrating cartilage matrix and bring about endochondral bone formation. This results in the formation of a nutrient foramen which is retained as the vascular conduit between the exterior and interior of the bone. This study examined the dominant nutrient foramen of the neonatal ilium using high resolution micro-computed (micro-CT) tomography. Three-dimensional reconstruction of micro-CT data consistently demonstrated the presence of a distinctive, yet poorly reported, collar of bone extending into the trabecular cavity beyond the endosteum. This study proposes that this collar of bone may have formed in response to osteogenic signaling from approximated arterial vasculature. Additionally, it is suggested that the formation of this collar may act as a protective mechanism to the dominant nutrient vessel and as a potential biomechanical anchor for surrounding trabeculae, aiding to increase the biomechanical competency around the area of the foramen. The documentation of this osteological structure is important from a clinical perspective to prevent the misinterpretation of fracturing and pathology on plain plate radiographs and clinical computed tomography scans.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".