Bibliographic record
Abstract
No AccessUrology Practicethe Specialty1 Mar 2017Editorial Commentary Christopher R. Porter and Mazen Alsinnawi Christopher R. PorterChristopher R. Porter More articles by this author and Mazen AlsinnawiMazen Alsinnawi More articles by this author View All Author Informationhttps://doi.org/10.1016/j.urpr.2016.04.011AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail "Editorial Commentary." Urology Practice, 4(2), p. 168 References 1 : Canadian guidelines for the management of small renal masses (SRM). Can Urol Assoc J2015; 9: 160. Google Scholar 2 : VHL and HIF-1α gene variations and prognosis in early-stage clear cell renal cell carcinoma. Med Oncol2014; 31: 840. Google Scholar © 2017 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 4Issue 2March 2017Page: 168 Advertisement Copyright & Permissions© 2017 by American Urological Association Education and Research, Inc.MetricsAuthor Information Christopher R. Porter More articles by this author Mazen Alsinnawi 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 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.015 | 0.014 |
| Insufficient payload (model declined to judge) | 0.099 | 0.046 |
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".