Bibliographic record
Abstract
No AccessUrology PracticeHealth Policy1 Sep 2015Editorial Commentary Sender Herschorn Sender HerschornSender Herschorn View All Author Informationhttps://doi.org/10.1016/j.urpr.2014.11.011AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail "Editorial Commentary." Urology Practice, 2(5), p. 233 References 1 Ipsos-Reid/Canadian Medical Association poll, February 2004. Available at http://www.ipsos-na.com/news-polls/searchresults.aspx?search=Ipsos-Reid/Canadian+Medical+Association+February+2004. Accessed January 14, 2015. Google Scholar 2 Health Canada: A 10-year plan to strengthen health care. September 16, 2004. Available at http://www.ipsos-na.com/news-polls/searchresults.aspx?search=Ipsos-Reid/Canadian+Medical+Association+February+2004. Accessed January 14, 2015. Google Scholar 3 Ontario Ministry of Health and Long-Term Care: Ontario Wait Times 2015. Available at http://www.ontariowaittimes.com/SurgeryDI/EN/Type.aspx?view=1. Accessed January 14, 2015. Google Scholar 4 Canadian Institute for Health Information: Health Care in Canada, 2012: A Focus on Wait Times. Ottawa: CIHI 2012. Google Scholar © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 2Issue 5September 2015Page: 233 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Sender Herschorn 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 | 0.011 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.020 | 0.016 |
| Insufficient payload (model declined to judge) | 0.245 | 0.117 |
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".