Bibliographic record
Abstract
As mentioned in our study,2 all patients were initially investigated by urine cytology, which were all negative. Similarly, Feifer and colleagues4 found that for patients with MH, voided urine cytology added a significant cost without any diagnostic benefit in the workup for low-risk patients. In their study, it was shown that of 200 patients, 8 (4%) had low-grade urothelial bladder cancer via cystoscopy (Ta or T1 tumours). Of these 8 patients, the cytology was negative in 4 patients and atypical in 4. These cases were asymptomatic contrary to our patients with lower urinary tract symptoms. The economic study referred to by Tin and colleagues was a retrospective study depending on data collection of cases presented in 2003 and 2004 and still confirmed the role of cystoscopy, following negative cytology. We found that 20% of our cases presented with MH had negative urine cytology, negative findings in multiphasic computed tomography, and positive cystoscopic finding – this number of close to those presenting with gross hematuria. This confirms the importance of cystoscopy as an initial diagnostic tool for high-grade MH.
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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 | 0.157 | 0.553 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.005 |
| Science and technology studies | 0.003 | 0.026 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.024 | 0.017 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".