Bibliographic record
Abstract
The attainment of a satisfactory peak bone mass, which is accomplished largely by the end of adolescence, is the best protection against excessive bone mineral loss in late adulthood. Factors that influence this process include age, race, sex, body size, pubertal status, diet, physical activity, and other lifestyle elements. Cancer and its treatment in children and teenagers adversely impact bone mineralization. In particular, chemotherapy (especially glucocorticosteroids and methotrexate) and cranial irradiation (apparently by reducing growth hormone secretion and by causing hypogonadotropic hypogonadism) interfere with normal bone turnover. Resorption often exceeds formation, resulting in net bone mineral loss and providing a rational basis for the use of antiresorptive drugs. Such osteopenia may be symptomatic, with pain and abnormal gait, and increases the risk of fractures several fold. The disorder is compounded by reduced physical activity, so programs to reduce this deficit are of measurable benefit. All of those engaged in the care of children and adolescents with cancer have an opportunity to improve the bone health of these young people and to limit their risk of developing osteoporosis and fragility fractures in adult life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".