Bibliographic record
Abstract
T he landscape for the treatment of metastatic prostate cancer has changed drastically in the past several years, with a much broader armamentarium of options for patients.Where androgen deprivation therapy (ADT) was once the gold standard, new approaches include androgen receptor pathway inhibitors (ARPis), docetaxel chemotherapy, and combinations thereof.The uptake on these lifeprolonging approaches in the castration-sensitive setting by the urologic community worldwide has been low and slow.As noted by CUA past-President, Armen Aprikian, in his 20022 CUAJ editorial, there could be several possible explanations for this, including provincial access issues, the administrative burden of closer side effect monitoring, and the overall burden in the management of patients with complex health issues.The CUA felt strongly that this care gap needed to be urgently addressed and launched a multipronged educational campaign.In October 2023, we hosted a national "Call to Action" meeting that featured a review of the latest data on mCSPC treatment intensification, followup strategies and side effect management, and sequencing after progression, as well as talks on genetic testing, PSMA-PET testing, and evaluation and management of oligometastatic disease.Following the meeting, the CUA, along with a panel of national experts, developed highly
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 | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.022 | 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".