Bibliographic record
Abstract
The mass of growing bones increases through changes in outer dimensions and through the net addition of tissue on inner bone surfaces. In this overview I examine bone accrual as it occurs on trabecular (inner) and periosteal (outer) surfaces. In the axial skeleton, the amount of trabecular bone increases during development, because trabeculae grow thicker as a result of bone remodeling with a positive balance. Remodeling is a process in which osteoblasts and osteoclasts are tightly linked ("coupled") in time and space. In contrast to trabecular thickness, trabecular number and material density change little throughout development. Bone accrual on periosteal surfaces leads to an increase in bone size, which is a crucial determinant of bone strength throughout life. Periosteal osteoblasts deposit new bone on an extended surface area and over an extended period of time without being interrupted by osteoclasts. This type of bone metabolic activity is called modeling, which is much more efficient than remodeling for increasing bone mass. In the past, research has focused on bone remodeling on trabecular surfaces. However, the key to an improved understanding of bone mass and strength development in children will lie with studies on bone modeling on periosteal surfaces.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".