Bibliographic record
Abstract
Letters18 October 2016Hematuria as a Marker of Occult Urinary Tract CancerMatthew Nielsen, MD, MS and Amir Qaseem, MD, PhDMatthew Nielsen, MD, MSFrom University of North Carolina Lineberger Comprehensive Cancer Center, Chapel Hill, North Carolina, and American College of Physicians, Philadelphia, Pennsylvania.Search for more papers by this author and Amir Qaseem, MD, PhDFrom University of North Carolina Lineberger Comprehensive Cancer Center, Chapel Hill, North Carolina, and American College of Physicians, Philadelphia, Pennsylvania.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/L16-0328 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail IN RESPONSE:Dr. Brown's first point addressing cases where the clinical presentation suggests glomerular sources is well-taken. As we discussed, current guidelines differ in their recommendations for evaluation of patients with hematuria who have findings suggestive of potential nephrologic disorders, such as hypertension, renal insufficiency, cellular casts, proteinuria, or dysmorphic erythrocytes. The American Urological Association and British Association of Urological Surgeons recommend concurrent nephrologic and urologic evaluation in this context, whereas the Canadian and Dutch guidelines suggest referral to a nephrologist as an alternative starting point. We also noted in the Limitations of the Evidence section that such presentations logically ... Author, Article, and Disclosure InformationAffiliations: From University of North Carolina Lineberger Comprehensive Cancer Center, Chapel Hill, North Carolina, and American College of Physicians, Philadelphia, Pennsylvania.Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M15-1496. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoHematuria as a Marker of Occult Urinary Tract Cancer: Advice for High-Value Care From the American College of Physicians Matthew Nielsen , Amir Qaseem , and Hematuria as a Marker of Occult Urinary Tract Cancer Robert S. Brown Metrics Cited byCancer Prevalence and Risk Stratification in Adults Presenting With Hematuria: A Population-Based Cohort StudyGuideline of guidelines: asymptomatic microscopic haematuria 18 October 2016Volume 165, Issue 8Page: 602KeywordsBladder cancerCystoscopyDisclosureHypertensionMedical risk factorsNephrologyProteinuriaSurgeonsUrology ePublished: 18 October 2016 Issue Published: 18 October 2016 Copyright & PermissionsCopyright © 2016 by American College of Physicians. All Rights Reserved.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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".