Key concerns about the current state of bladder cancer
Bibliographic record
Abstract
Bladder cancer is the fifth most common cancer in the United States and, on a per capita basis, is the most expensive cancer from diagnosis to death. Unfortunately, National Cancer Institute funding for bladder cancer is quite low when compared with other common malignancies. Limited funding has stifled research opportunities for new and established investigators, ultimately encouraging them to redirect research efforts to other organ sites. Waning interest of scientists has further fueled the cycle of modest funding for bladder cancer. One important consequence of this has been a lack of scientific advancement in the field. Patient advocates have decidedly advanced research efforts in many cancer sites. Breast, prostate, pancreatic, and ovarian cancer advocates have organized highly successful campaigns to lobby the federal government and the medical community to devote increased attention and funding to understudied malignancies and to conduct relevant studies to better understand the therapy, diagnosis, and prevention of these diseases. Bladder cancer survivors have lacked a coordinated advocacy voice until recently. A concerted effort to align bladder cancer advocates, clinicians, and urologic organizations is essential to define the greatest needs in bladder cancer and to develop related solutions. This position paper represents a collaborative discussion to define the most concerning trends and greatest needs in the field of bladder cancer as outlined by the Bladder Cancer Think Tank, the Bladder Cancer Advocacy Network, and the Society of Urologic Oncology.
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 | 0.011 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.010 | 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".