Impact of Implementing the Paris System for Reporting Urine Cytology in the Performance of Urine Cytology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: We assessed the performance of urine cytology using the Paris System for Reporting Urine Cytology (PSRUC) in comparison to our current system. METHODS: In total, 124 specimens with histologic correlation were reviewed and assigned to the PSRUC categories: benign, atypical urothelial cells (AUCs), suspicious for high-grade urothelial carcinoma (SHGUC), and high-grade urothelial carcinoma (HGUC). Original cytological diagnoses were recorded. RESULTS: Fewer cases were given an AUC diagnosis using the PSRUC in comparison to the original diagnoses (26% vs 39%), while the association of AUCs with subsequent HGUC increased from 33% to 53% with the PSRUC. Using the PSRUC resulted in a higher number of low-grade carcinomas assigned to the benign (40%) rather than the AUC (22%) category. The performance of SHGUC/HGUC diagnoses was similar in both systems (predictive value = 94%). CONCLUSIONS: The PSRUC seems to improve the performance of urine cytology by limiting the AUC category to cases that are more strongly associated with HGUC.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it