Bibliographic record
Abstract
Introduction This chapter deals with pediatric disorders which are characterized by increased bone fragility and decreased bone mass. Compared with adults, such diseases are relatively rare in children, but may have devastating consequences. Osteoporosis can occur as a primary bone disorder or may be secondary to other diseases and/or their treatment (Table 13.1). The primary forms of childhood osteoporosis comprise osteogenesis imperfecta and idiopathic juvenile osteoporosis. Secondary pediatric osteoporosis is most frequently seen as a consequence of immobilization and of long-term steroid treatment in a variety of chronic diseases. Osteogenesis imperfecta Osteogenesis imperfecta (OI), also called brittle bone disease, is a hereditary form of osteoporosis. In many patients the disease is due to abnormalities in collagen type I. Therefore, the disease manifests itself not only in bone, but also in other tissues that contain collagen type I, such as skin, teeth and sclerae. OI is thought to affect between 1/10000 and 1/15000 individuals of all racial and ethnic origins (Byers & Steiner, 1992). Clinical presentation Family history In most familial cases of OI, heredity follows an autosomal dominant pattern. However, new mutations are frequent, especially in the more severe forms. There may also be germline mosaicism for OI mutations, so that unaffected parents can have more than one affected child (Rowe & Shapiro, 1998).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.045 | 0.012 |
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".