Capturing recurrence in urothelial carcinoma: “more than meets the eye”
Bibliographic record
Abstract
Urothelial carcinoma is the sixth most common cancer in the United States and is a significant source of mortality worldwide (1). Bladder urothelial carcinoma is a molecularly heterogeneous malignancy that typically presents as an exophytic tumour (or flat carcinoma in situ ) confined to the mucosa or lamina propria (NMIBC); however, up to a third of patients have muscle-invasive (MIBC) and about 4% metastatic disease (mUC) at the time of diagnosis (2). While platinum-based chemotherapy has been the cornerstone of therapy for a long time, significant progress has been made recently in the treatment armamentarium of mUC, particularly with immune checkpoint and fibroblast growth factor receptor (FGFR) inhibition (3). For MIBC, neoadjuvant cisplatin-based chemotherapy has been shown to improve overall survival and thus is considered the standard of care prior to definitive locoregional therapy (4). Given the morbidity and mortality associated with mUC, optimizing early detection of recurrence after definitive therapy remains a very important, unmet need.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".