Re: Adjuvant Radiotherapy for Pathological T3N0M0 Prostate Cancer Significantly Reduces Risk of Metastases and Improves Survival: Long-Term Followup of a Randomized Clinical Trial
Bibliographic record
Abstract
No AccessJournal of UrologyLetter to the Editor/Errata1 Nov 2009Re: Adjuvant Radiotherapy for Pathological T3N0M0 Prostate Cancer Significantly Reduces Risk of Metastases and Improves Survival: Long-Term Followup of a Randomized Clinical TrialI. M. Thompson, C. M. Tangen, J. Paradelo, M. S. Lucia, G. Miller, D. Troyer, E. Messing, J. Forman, J. Chin, G. Swanson, E. Canby-Hagino and E. D. Crawford J Urol 2009; 181: 956–962 Tina Cheng, Daniel Y. Heng, and Douglas Stewart Tina ChengTina Cheng More articles by this author , Daniel Y. HengDaniel Y. Heng More articles by this author , and Douglas StewartDouglas Stewart More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2009.07.053AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail References 1 : Adjuvant radiotherapy for pathologically advanced prostate cancer: a randomized clinical trial. JAMA2006; 296: 2329. Google Scholar 2 : Postoperative radiotherapy after radical prostatectomy: a randomised controlled trial (EORTC trial 22911). Lancet2005; 366: 572. Google Scholar Department of Medical Oncology and Medicine, University of Calgary, Calgary, Alberta, Canada© 2009 by American Urological AssociationFiguresReferencesRelatedDetails Volume 182Issue 5November 2009Page: 2531-2534 Advertisement Copyright & Permissions© 2009 by American Urological AssociationMetricsAuthor Information Tina Cheng More articles by this author Daniel Y. Heng More articles by this author Douglas Stewart More articles by this author Expand All Advertisement PDF downloadLoading ...
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
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".