Management of carcinoma of the penis: Consensus statement from the Canadian Association of Genitourinary Medical Oncologists (CAGMO)
Bibliographic record
Abstract
and uro-oncology was also incorporated into the consensus statement.The manuscript was evaluated using the AGREEII instrument. 9A planned update will occur in 5 years. Penile cancer risk factorsThe main risk factors for penile cancer with an odds ratio >10 include phimosis, chronic inflammatory conditions of the penis, treatment with psoralen and ultraviolet A phototherapy, a history of multiple sexual partners, and early age at first intercourse. 10History of condylomata is associated with a 6-fold increase in the risk of penile cancer. 10History of smoking is associated with a 3-to 4.5-fold increase in risk and is an independent risk factor regardless of sexual history. 10 CircumcisionCircumcision is a controversial issue that weighs the rights for individual choice and potential for disease prevention against the risk of complications and cost-effectiveness of a population-based program.Although several series and a meta-analysis support a reduction in both Human papilloma virus (HPV) and penile cancer prevalence with circumcision, 11-14 routine neonatal circumcision has been delisted in every province across Canada due to an unfavourable benefit-to-harm ratio.
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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 | 0.025 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| 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".