Osteoporosis after blood and marrow transplantation: Clinical aspects
Bibliographic record
Abstract
Abstract As the number of long-term survivors of bone marrow transplantation (BMT) increases, attention must turn to the late complications of this procedure. One such late complication is osteoporosis, a decrease in skeletal bone mass. In the short term, osteoporosis seems trivial compared with a diagnosis of cancer, but for those cured of their disease, this condition contributes to chronic morbidity and mortality. For example, hip fractures resulting from osteoporosis are associated with long periods of immobility, and they restrict the patient's lifestyle. Fifty percent of patients who sustain an osteoporosis-related hip fracture require assistance with activities of daily living, and 25% require placement in long-term care facilities [1]. Osteoporotic hip fractures also affect patient mortality. Elderly patients who suffer an osteoporosis-related hip fracture have an increased 1-year mortality rate of 12% to 37% [2]. Early recognition and treatment of osteoporosis should therefore be integral components of the follow-up of long-term BMT survivors. Biol Blood Marrow Transplant 2000;6(2A):175-81.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".