COEXISTING PROSTATE CANCER FOUND AT THE TIME OF HOLMIUM LASER ENUCLEATION OF THE PROSTATE FOR BENIGN PROSTATIC HYPERPLASIA: PREDICTING ITS PRESENCE AND GRADE IN ANALYZED TISSUE
Bibliographic record
Abstract
Abstract Objective: To determine the incidence of prostate cancer identified on holmium laser enucleation of the prostate (HoLEP) specimens and evaluate variables associated with prostate cancer identification. Patients and Methods: All patients undergoing HoLEP between 1998 and 2013 were identified. Patients with a known history of prostate cancer were excluded. Multivariable logistic regression assessed variables associated with identification of prostate cancer on HoLEP specimens and Gleason 7 or higher prostate cancer among the malignant cases. The Gleason grade was used as a proxy for disease severity. Each of the models was adjusted for age, preoperative prostate-specific antigen (PSA), and HoLEP specimen weight. Results: The cohort comprised 1272 patients, of whom 103 (8.1%) had prostate cancer identified. Prostate cancer cases had higher pre-HoLEP PSA (p=0.06) but lower HoLEP specimen weight (p=0.01). On multivariate logistic regression, age and preoperative PSA were associated with increased odds...
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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 | 0.001 | 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 | 0.000 | 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 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".