The Results of Radical Nephrectomy for Renal Cell Carcinoma
Bibliographic record
Abstract
No AccessJournal of Urology1 Feb 2017The Results of Radical Nephrectomy for Renal Cell Carcinoma Charles J. Robson, Bernard M. Churchill, and William Anderson Charles J. RobsonCharles J. Robson , Bernard M. ChurchillBernard M. Churchill , and William AndersonWilliam Anderson View All Author Informationhttps://doi.org/10.1016/j.juro.2016.10.095AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail References 1 Bloom, H. J. and Wallace, D. M.: Hormones and the kidney: possible therapeutic role of testosterone in a patient with regression of metastases from renal adenocarcinoma. Brit. Med. J., 2: 476, 1964. Google Scholar 2 Bloom, H. J. G., Baker, W. H., Dukes, C. E. and Mitchley, B. C. V.: Hormone-dependent tumours of the kidney. II. Effect of endocrine ablation procedures on the transplanted oestrogen-induced renal tumour of the Syrian hamster. Brit. J. Cane., 17: 646, 1963. Google Scholar 3 Chute, R., Soutter, L. and Kerr, W. S., Jr.: Value of thoracoabdominal incision in removal of kidney tumors. New Engl. J. Med., 241: 951, 1949. Google Scholar 4 Mortensen, H.: Transthoracic nephrectomy. J. Urol., 60: 855, 1948. Google Scholar 5 Robson, C. J.: Radical nephrectomy for renal cell carcinoma. J. Urol., 89: 37, 1963. Google Scholar 6 Flocks, R. H. and Kadesky, M. C.: Malignant neoplasms of the kidney: an analysis of 353 patients followed 5 years or more. J. Urol., 79: 196, 1958. Google Scholar 7 Petkovic, S. A.: An anatomical classification of renal tumors in the adult as a basis for prognosis. J. Urol., 81: 618, 1959. Google Scholar 8 Riches, E.: Tumors of the Kidney and Ureter. Baltimore: The Williams & Wilkins Co., 1964. Google Scholar 9 Riches, E.: On carcinoma of the kidney. Ann. Roy. Coll. Surg., 32: 201, 1963. Google Scholar 10 Priestly, J. T.: Survival following the removal of malignant renal neoplasms. J. A. M. A., 113: 992, 1939. Google Scholar 11 Riches, E., Griffiths, J. H. and Thackray, A. C.: New growths of the kidney and ureter. Brit. J. Urol., 23: 297, 1951. Google Scholar 12 Kaufman, J. J. and Mims, M. M.: Tumors of the kidney. In: Current Problems in Surgery, February 1966. Google Scholar © 2002 by American Urological Association, Inc.®FiguresReferencesRelatedDetails Volume 197Issue 2SFebruary 2017Page: S111-S113 Advertisement Copyright & Permissions© 2002 by American Urological Association, Inc.®MetricsAuthor Information Charles J. Robson More articles by this author Bernard M. Churchill More articles by this author William Anderson 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".