The results of radical nephrectomy for renal cell carcinoma
Bibliographic record
Abstract
No AccessJournal of Urology1 Feb 2002The results of radical nephrectomy for renal cell carcinoma Charles J. Robson, Bernard M. Churchill, and William Anderson Charles J. RobsonCharles J. Robson Divison of Urology, Department of Surgery University of Toronto, Ontario, Canada. Department of Pathology, University of Toronto, Ontario, Canada , Bernard M. ChurchillBernard M. Churchill Divison of Urology, Department of Surgery University of Toronto, Ontario, Canada. Department of Pathology, University of Toronto, Ontario, Canada , and William AndersonWilliam Anderson Divison of Urology, Department of Surgery University of Toronto, Ontario, Canada. Department of Pathology, University of Toronto, Ontario, Canada View All Author Informationhttps://doi.org/10.1016/S0022-5347(02)80286-5AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail A series of 88 cases of renal cell carcinoma treated by radical nephrectomy is presented showing a statistically significant improvement in the 3,5 and 10-year survival rates. This increased survival rate is due to 3 factors: 1) early ligation of the renal artery and vein, 2) complete removal of the perinephric envelope and 3) surgical extirpation of the lymphatic field. Prognosis is directly related to the stage and grade of the tumor. Some ancillary aids in the preoperative prognostic evaluation of the tumor are suggested and discussed. © 2002 by American Urological Association, IncFiguresReferencesRelatedDetailsCited byMarley C, Siegrist T, Kurta J, O'Brien F, Bernstein M, Solomon S and Coleman J (2018) Cold Intravascular Organ Perfusion for Renal Hypothermia During Laparoscopic Partial NephrectomyJournal of Urology, VOL. 185, NO. 6, (2191-2195), Online publication date: 1-Jun-2011.Siddiqui S, Frank I, Leibovich B, Cheville J, Lohse C, Zincke H and Blute M (2018) Impact of Tumor Size on the Predictive Ability of the pT3a Primary Tumor Classification for Renal Cell CarcinomaJournal of Urology, VOL. 177, NO. 1, (59-62), Online publication date: 1-Jan-2007. Volume 167Issue 2 Part 2February 2002Page: 873-875 Advertisement Copyright & Permissions© 2002 by American Urological Association, IncMetricsAuthor Information Charles J. Robson Divison of Urology, Department of Surgery University of Toronto, Ontario, Canada. Department of Pathology, University of Toronto, Ontario, Canada More articles by this author Bernard M. Churchill Divison of Urology, Department of Surgery University of Toronto, Ontario, Canada. Department of Pathology, University of Toronto, Ontario, Canada More articles by this author William Anderson Divison of Urology, Department of Surgery University of Toronto, Ontario, Canada. Department of Pathology, University of Toronto, Ontario, Canada More articles by this author Expand All Advertisement PDF downloadLoading ...
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".