Bibliographic record
Abstract
Canada’s Drug Agency (CDA-AMC) recommends that Balversa should be reimbursed by public drug plans for the treatment of locally advanced unresectable or metastatic urothelial carcinoma (UC) if certain conditions are met. Balversa should only be covered to treat patients with a diagnosis of locally advanced unresectable or metastatic UC harbouring susceptible FGFR3 genetic alterations who have disease progression during or following at least 1 line of prior therapy. Patients who experience disease recurrence within 12 months after chemotherapy before surgery (neoadjuvant) or following the removal of the bladder (adjuvant) are also eligible to receive Balversa. In patients who qualify for treatment with PD-1 or PD-L1 inhibitor, Balversa should only be reimbursed after patients have received PD-1 or PD-L1 therapy. Balversa should only be reimbursed if it is prescribed by a clinician with expertise in treating patients with UC with susceptible FGFR3 genetic alteration confirmed using a validated test. The price of Balversa should be reduced. It must also be feasible to test patients for FGFR3 genetic alterations.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.014 |
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".