Circumcision and Risk of HIV among Males from Ontario, Canada. Reply.
Bibliographic record
Abstract
No AccessJournal of UrologyLetters to the Editor1 Feb 2022Circumcision and Risk of HIV among Males from Ontario, Canada. Reply.is a reply to letterCircumcision and Risk of HIV among Males from Ontario, Canada. Letter. M. Nayan, R. J. Hamilton, D. N. Juurlink, P. C. Austin, and K. A. Jarvi M. NayanM. Nayan * E-mail Address: [email protected]; E-mail Address: [email protected] Division of Urology, Departments of Surgery and Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, Ontario, Canada , R. J. HamiltonR. J. Hamilton Division of Urology, Departments of Surgery and Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, Ontario, Canada , D. N. JuurlinkD. N. Juurlink ICES, Toronto, Ontario, Canada Departments of Medicine and Pediatrics, University of Toronto, Toronto, Ontario, Canada , P. C. AustinP. C. Austin ICES, Toronto, Ontario, Canada , and K. A. JarviK. A. Jarvi Division of Urology, Department of Surgery, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada Faculty of Medicine, Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada Lunenfeld Tannenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada View All Author Informationhttps://doi.org/10.1097/JU.0000000000002338AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail "Circumcision and Risk of HIV among Males from Ontario, Canada. Reply.." The Journal of Urology, 207(2), pp. 479–480 References 1. : Circumcision and risk of HIV among males from Ontario, Canada. J Urol 2022; 207: 424. Link, Google Scholar © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetailsRelated articlesJournal of UrologyNov 15, 2021, 12:00:00 AMCircumcision and Risk of HIV among Males from Ontario, Canada. Letter. Volume 207Issue 2February 2022Page: 479-480 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information M. Nayan Division of Urology, Departments of Surgery and Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, Ontario, Canada * E-mail Address: [email protected]; E-mail Address: [email protected] More articles by this author R. J. Hamilton Division of Urology, Departments of Surgery and Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, Ontario, Canada More articles by this author D. N. Juurlink ICES, Toronto, Ontario, Canada Departments of Medicine and Pediatrics, University of Toronto, Toronto, Ontario, Canada More articles by this author P. C. Austin ICES, Toronto, Ontario, Canada More articles by this author K. A. Jarvi Division of Urology, Department of Surgery, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada Faculty of Medicine, Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada Lunenfeld Tannenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.017 | 0.011 |
| Insufficient payload (model declined to judge) | 0.014 | 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".