Re: Pretreatment Total Testosterone Level Predicts Pathological Stage in Patients With Localized Prostate Cancer Treated With Radical Prostatectomy
Bibliographic record
Abstract
No AccessJournal of UrologyCLINICAL UROLOGY: Letters to the Editor1 Dec 2003Re: Pretreatment Total Testosterone Level Predicts Pathological Stage in Patients With Localized Prostate Cancer Treated With Radical Prostatectomy Rabi Tiguert, and Brant A. Inman Rabi TiguertRabi Tiguert More articles by this author , and Brant A. InmanBrant A. Inman More articles by this author View All Author Informationhttps://doi.org/10.1097/01.ju.0000095148.84868.baAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail "Re: Pretreatment Total Testosterone Level Predicts Pathological Stage in Patients With Localized Prostate Cancer Treated With Radical Prostatectomy." The Journal of Urology, 170(6), p. 2392 References 1 : Handbook for staging of cancer. In: AJCC Manual for Staging of Cancer. Philadelphia: J. B. Lippincott Co.1992: 189. Google Scholar 2 : TNM Classification of Malignant Tumours. New York: Wiley-Liss1997: 172. Google Scholar 3 : TNM Classification of Malignant Tumours. New York: Wiley-Liss2002: 184. Google Scholar Division of Urology, Centre de Recherche L’Hôtel Dieu Québec, Centre Hospitalier universitaire de Québec, 11, Côte du Palais, Québec, Canada G1R2J6© 2003 by American Urological Association, Inc.FiguresReferencesRelatedDetails Volume 170Issue 6December 2003Page: 2392 Advertisement Copyright & Permissions© 2003 by American Urological Association, Inc.MetricsAuthor Information Rabi Tiguert More articles by this author Brant A. Inman 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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".