Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it