Novel Technique of Sampling the Urinary Bladder for Urothelial Carcinoma Specimens
Bibliographic record
Abstract
Sampling of the urinary bladder (UB) in radical cystectomy specimens is usually performed by obtaining sections through the lesions taken in rather random planes. The technique is hindered by the difficulty in identifying the anatomical relationship of the tumor with the remaining urinary bladder. Fifty radical cystectomy specimens were bisected in the horizontal plane at the middle portion of the UB then fixed without tissue stretching in 10% buffered formalin for at least 24 hours. The UBs were serially sectioned in parallel horizontal planes from the UB neck to the dome into rings of 3 to 10 mm thickness. The sections were orderly arranged and photographed. At least one ring of tissue was entirely submitted along with areas of interest or representative areas. Our proposed technique of transverse sections results in a mild increase in the number of sections submitted for microscopic examination. The advantages of our methods are (a) consistency and ease of sampling that help the microscopic-macroscopic correlation, (b) suitability for gross examination and for determining depth of invasion and largest tumor diameter, (c) improved identification of satellite lesions, and (d) suitability for neoplastic mapping and suitability for reexamination. The technique was validated by comparing with results of current technique.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".