Bibliographic record
Abstract
delivery and clinical experience have improved tumour and toxicity outcomes, particularly for brachytherapy and cryotherapy, which have the longest history and are the most extensively investigated.Similarly, appropriate patient selection is critical for a favourable outcome, since none of these modalities can safely and reliably treat very far beyond the prostate capsule, and they are all best limited to the treatment of patients with low-risk disease.The paper by Chalasani and colleagues 1 in this edition of CUAJ brings our attention to cryotherapy, which, as the authors state, has a very long history somewhat marred by severe toxicity in the early experience.However, better patient selection, newer technology and the application of the principles outlined above have improved outcomes in more recent reports. 2 The authors do not provide any clinical data, but rather a description of a third-generation ultrasonography unit that provides real-time 3-dimensional visualization of the procedure.They predict that this will lead to improved precision and better outcomes, although this needs confirmation in clinical trials.Prostate brachytherapy remains the gold standard for minimally invasive therapy because the toxicity profile and tumour outcomes for appropriately selected patients are predictable and favourable, having been well documented in large-scale prospective trials.Cryotherapy and the other minimally invasive modalities hold promise but all must be rigorously scrutinized in large-scale prospective trials before being accepted as standard therapy.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".