Bibliographic record
Abstract
Androgen deprivation therapy (ADT) is standard for advanced prostate cancer and is now increasingly used as adjunct therapy in high-risk or locally advanced disease and for the treatment of recurring disease based on rising prostate-specific antigen levels. Testosterone stimulates bone formation directly by stimulating the osteoblast proliferation, inhibiting the apoptosis of both osteoblasts and osteoclasts, and indirectly by being a precursor of oestrogen which is also involved in inhibiting osteoclastic function (bone resorption). The effects of testosterone on preserving bone health are lost in the hypogonadal state induced by ADT [1]. The impact of ADT on bone loss and osteoporosis is well established through multiple studies. In one of these studies, non-metastatic prostate cancer cases were followed for 10 years; none of the patients on ADT had normal bone mass density (BMD) at the end of the study, and the prevalence of osteoporosis (T score < −2.5) was approximately 50% by 4 years and 80% by 10 years in men on ADT [2]. Bone metastases will occur in over 90% of men with lethal castration-resistant prostate cancer (CRPC). Due to the combined effect of bone fragility due to ADT and the presence of bone metastases, almost all patients will experience some form of morbidity related to bone metastases prior to succumbing from the disease. Complications go beyond pain and include pathological fracture, the need for palliative radiation or surgery, and spinal cord compression. These events impair quality of life and place a significant burden on health-care resources.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".