Cystic Nephroma of the Kidney
Bibliographic record
Abstract
No AccessJournal of UrologyPathology Page1 Jan 2015Cystic Nephroma of the Kidney Samay Jain, Sri Krishna Chaitanya Arudra, and Luis E. De Las Casas Samay JainSamay Jain More articles by this author , Sri Krishna Chaitanya ArudraSri Krishna Chaitanya Arudra More articles by this author , and Luis E. De Las CasasLuis E. De Las Casas More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.10.047AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail "Cystic Nephroma of the Kidney." The Journal of Urology, 193(1), pp. 313–314 References 1 : Cystic nephroma. In: World Health Organization Classification of Tumours. Pathology and Genetics of Tumours of the Urinary System and Male Genital Organs. Edited by . Lyon: IARC Press2004: 76. Google Scholar 2 : Cystic nephroma and mixed epithelial and stromal tumor of kidney: a detailed clinicopathologic analysis of 34 cases and proposal for renal epithelial and stromal tumor (REST) as a unifying term. Am J Surg Pathol2007; 31: 489. Google Scholar 3 : The International Society of Urological Pathology (ISUP) Vancouver Classification of Renal Neoplasia. Am J Surg Pathol2013; 37: 1469. Google Scholar © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 1January 2015Page: 313-314 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.Metrics Author Information Samay Jain More articles by this author Sri Krishna Chaitanya Arudra More articles by this author Luis E. De Las Casas 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.006 |
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".