Bibliographic record
Abstract
Current Opinion in Urology was launched in 1991. It is one of a successful series of review journals whose unique format is designed to provide a systematic and critical assessment of the literature as presented in the many primary journals. The field of urology is divided into 12 sections that are reviewed once a year. Each section is assigned a Section Editor, a leading authority in the area, who identifies the most important topics at that time. Here we are pleased to introduce the Section Editor for this issue. SECTION EDITOR Željko KikićŽeljko KikićŽeljko Kikić received his MD degree from the Medical University of Vienna, Austria in 2007. From 2007 he was trained at the Div. of Nephrology and Dialysis, Medical University of Vienna, Austria where he obtained licenses for Internal Medicine (2013), Nephrology (2015) and intensive care medicine (2017). Since 2016 he is a professor for medicine and senior physician. In 2020 he has become the leader of the pre-operative medicine unit at the Department of Urology, Medical University of Vienna, Austria and of the interdisciplinary Board on Urolithiasis, Department of Urology, Medical University of Vienna, Austria. Željko Kikić has conducted numerous studies in the field of transplantation with continued focus on typical and atypical C4d staining patterns, antibody-mediated rejection, salt-losing tubolopathies and Polyoma Nephropathy. Highlights of recent work: establishment of diffuse extent of peritubular capillaritis as an independent risk factor for graft loss, research on the clinical relevance on atypical C4d staining patterns, and project leader of a randomized trial to examine the impact of haemodialysis and citrate anticoagulation on delayed graft function. In 2020 he was named WG leader of the BANFF WG on peritubular capillaritis. International network: WG leader of the BANFF WG on peritubular capillaritis, Scientific cooperations with Alberta renal pathology Working group in Canada (Chair: Dr Michael Mengel).
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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 | 0.004 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.162 | 0.088 |
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".