3rd Pavia international symposium on advanced kidney cancer
Bibliographic record
Abstract
Kidney cancers' natural history has radically changed in the past few years, due to the development of novel targeted agents. Despite these improvements, several unanswered questions still remain on the table, regarding the best first-line treatment, the ideal sequence of treatments, the management of specific subgroups of patients (e.g., elderly patients or those with comorbidities) and the relevance of prognostic factors, among many others. To foster discussions among clinicians and investigators working in this field, and to exchange different viewpoints concerning the newest advances in kidney cancer pathogenesis and treatment, the 3rd Pavia International Symposium on Advanced Kidney cancer was held in Pavia (Italy) between 30 June and 1 July 2011. The aim of this report is to summarize the most significant advances in the different disciplines applied to advanced kidney cancer, which were presented and discussed during the meeting, and how these advances will be changing the perspective of patients with this disease.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.010 |
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".