Accuracy of Urine Cytology and the Significance of an Atypical Category
Bibliographic record
Abstract
The "atypical urothelial cell" cytologic category is nonstandardized. We subclassify atypical cases to "atypical, favor a reactive process" or "atypical, unclear if reactive or neoplastic." We evaluated the predictive significance of atypical cases by looking at their histologic follow-up. Among the 1,114 patients and 3,261 specimens included, 282 specimens had histologic follow-up. An atypical diagnosis did not carry a significant increased risk of urothelial neoplasia compared with the benign category. Although an "atypical unclear" diagnosis carried a higher rate of detection of high-grade cancer on follow-up biopsy in comparison with "atypical reactive" or "negative" diagnoses (26/58 [45%] vs 15/52 [29%] and 16/103 [15.5%], respectively), this difference was not statistically significant. These results suggest that dividing atypical cases into 2 categories based on the level of cytologic suspicion of cancer does not add clinically relevant information within the atypical category. They also raise the question of the significance of the atypical category altogether.
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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 | 0.005 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".