Targeting androgen receptor signaling: a historical perspective
Bibliographic record
Abstract
The first case of prostate cancer was identified by histological examination by Adams, a surgeon at The London Hospital, in 1853. In his report, Adams noted that the condition was 'a very rare disease'. Now, over 150 years later, with increased life expectancy and screening, prostate cancer has become one of the most common cancers in men. In the United States alone, nearly 200,000 men are diagnosed with prostate cancer annually and about 33,000 succumb to their disease. Fifty years ago, men were typically diagnosed with prostate cancer in their seventies with disease that had metastasized to the bone and/or soft tissue. Diagnosis at such an advanced stage was a death sentence, with patients dying within 2 years. The pioneering work of Charles Huggins in the 1940s found that metastatic prostate cancer responds to androgen deprivation therapy (ADT), ushering in the rational use of hormone therapies that have irrevocably changed the course of prostate cancer disease management. Medical castration was the first effective systemic targeted therapy for any cancer and, to this day, androgen ablation remains the mainstay of prostate cancer therapy.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".