Bibliographic record
Abstract
No AccessJournal of UrologyAdult Urology1 Nov 2022Editorial CommentThis article comments on the following:Impact of Prostate Health Index Results for Prediction of Biopsy Grade Reclassification During Active Surveillance Christopher Morash Christopher MorashChristopher Morash *Email: E-mail Address: [email protected]; E-mail Address: [email protected]. Division of Urology, Surgical Oncology, University of Ottawa, Ottawa, Ontario, Canada More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002852.02AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail "Editorial Comment." The Journal of Urology, 208(5), p. 1045 References 1. The natural history of untreated biopsy grade group progression and delayed definitive treatment for men on active surveillance for early-stage prostate cancer. J Urol. 2022; 207(5):1001-1009 Link, Google Scholar 2. Active surveillance for men younger than 60 years or with intermediate-risk localized prostate cancer. Eur Urol Open Sci. 2022; 41:126-133. Google Scholar © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetailsRelated articlesJournal of Urology5 Jul 2022Impact of Prostate Health Index Results for Prediction of Biopsy Grade Reclassification During Active Surveillance Volume 208Issue 5November 2022Page: 1045-1045 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Christopher Morash Division of Urology, Surgical Oncology, University of Ottawa, Ottawa, Ontario, Canada *Email: E-mail Address: [email protected]; E-mail Address: [email protected]. 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 | 0.005 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.013 | 0.010 |
| Insufficient payload (model declined to judge) | 0.380 | 0.234 |
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".