Recommendations for the improvement of bladder cancer quality of care in Canada: A consensus document reviewed and endorsed by Bladder Cancer Canada (BCC), Canadian Urologic Oncology Group (CUOG), and Canadian Urological Association (CUA), December 2015
Bibliographic record
Abstract
This initiative was undertaken in response to concerns regarding the variation in management and in outcomes of patients with bladder cancer throughout centres and geographical areas in Canada. Population-based data have also revealed that real-life survival is lower than expected based on data from clinical trials and/or academic centres. To address these perceived shortcomings and attempt to streamline and unify treatment approaches to bladder cancer in Canada, a multidisciplinary panel of expert clinicians was convened last fall for a two-day working group consensus meeting. The panelists included urologic oncologists, medical oncologists, radiation oncologists, patient representatives, a genitourinary pathologist, and an enterostomal therapy nurse. The following recommendations and summaries of supporting evidence represent the results of the presentations, debates, and discussions. Methodology
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 | 0.155 | 0.156 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.016 | 0.008 |
| Research integrity | 0.013 | 0.020 |
| Insufficient payload (model declined to judge) | 0.004 | 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".