Bibliographic record
Abstract
Associate Editor Michael G. Wyllie Editorial Board Ian Eardley, UK Jean Fourcroy, USA Sidney Glina, Brazil Julia Heiman, USA Chris McMahon, Australia Bob Millar, UK Alvaro Morales, Canada Michael Perelman, USA Marcel Waldinger, Netherlands OBJECTIVE To assess whether the outcome of implanting penile prostheses is related to the number of prostheses implanted by surgeons, as several reports showed that the outcome of a urological procedure is directly related to the experience of the surgeon. METHODS We conducted a retrospective audit of 413 penile prostheses implanted over a 2‐year period in the UK by 76 surgeons. RESULTS About 80% of the surgeons implanted only one or two prostheses per year, usually of the malleable type, and usually on patients in the private sector. Only four surgeons implanted >20 prostheses per year. The overall revision rate for implantation in the UK, at 24%, is far higher than the worldwide average. CONCLUSIONS Guidelines are needed on the number of prostheses a surgeon should implant per year so that revision rates will decline to more acceptable levels and patients will be offered a genuine choice of product.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".