The Urinary Microbiome in Interstitial Cystitis/Bladder Pain Syndrome? A Critical Look at the Evidence
Bibliographic record
Abstract
No AccessJournal of UrologyJU Forum1 Nov 2021The Urinary Microbiome in Interstitial Cystitis/Bladder Pain Syndrome? A Critical Look at the Evidence Isobel Walton and J. Curtis Nickel Isobel WaltonIsobel Walton University of St. Andrews School of Medicine, Scotland, United Kingdom and J. Curtis NickelJ. Curtis Nickel †Correspondence: Department of Urology, Queen's University, Kingston Health Sciences Centre, 76 Stuart St., Kingston, Ontario, Canada K7L 2V7 telephone: 613-548-2497; E-mail Address: [email protected] http://orcid.org/0000-0002-4865-7293 Queen's University, Kingston, Canada View All Author Informationhttps://doi.org/10.1097/JU.0000000000001947AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail References 1. : Alterations of microbiota in urine from women with interstitial cystitis. BMC Microbiol 2012; 12: 205. Google Scholar 2. : The vaginal and urinary microbiomes in premenopausal women with interstitial cystitis/bladder pain syndrome as compared to unaffected controls: a pilot cross-sectional study. Front Cell Infect Microbiol 2019; 9: 92. Google Scholar 3. : Female lower urinary tract microbiota do not associate with IC/PBS symptoms: a case-controlled study. Int Urogynecol J 2019; 30: 1835. Google Scholar 4. : A culture-independent analysis of the microbiota of female interstitial cystitis/bladder pain syndrome participants in the MAPP research network. J Clin Med 2019; 8: 14. Google Scholar 5. : Urinary microbiome and cytokine levels in women with interstitial cystitis. Obstet Gynecol 2017; 129: 500. Google Scholar 6. : Cultivable bacteria in urine of women with interstitial cystitis: (not) what we expected. Female Pelvic Med Reconstr Surg 2021; 27: 322. Google Scholar Supported in part by the Canada Institutes of Health (CIHR) Canada Research Chair Progam (CRC) and University of St. Andrews, Scotland. © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue 5November 2021Page: 1087-1090 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.AcknowledgmentsSupported in part by the University of St. Andrews School of Medicine and the Canadian Institutes of Health Research (CIHR) Canada Research Chair (CRC) Program.MetricsAuthor Information Isobel Walton University of St. Andrews School of Medicine, Scotland, United Kingdom More articles by this author J. Curtis Nickel Queen's University, Kingston, Canada †Correspondence: Department of Urology, Queen's University, Kingston Health Sciences Centre, 76 Stuart St., Kingston, Ontario, Canada K7L 2V7 telephone: 613-548-2497; E-mail Address: [email protected] Previously received funding from NIH/NIDDK in the same field, but this present project was not funded by NIH/NIDDK. Current consultant and researcher for MicroGenDx. More articles by this author Expand All Supported in part by the Canada Institutes of Health (CIHR) Canada Research Chair Progam (CRC) and University of St. Andrews, Scotland. Advertisement PDF downloadLoading ...
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How this classification was reachedexpand
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 | 0.009 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".