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Record W3022052464 · doi:10.5489/cuaj.6697

Canadian Urological Association Best Practice Report: Catheter use

2020· article· en· W3022052464 on OpenAlexaffvenueabout
Lysanne Campeau, Samer Shamout, Richard Baverstock, Kevin Carlson, Dean Elterman, Duane Hickling, Stephen Steele, Blayne Welk

Bibliographic record

VenueCanadian Urological Association Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicUrinary Tract Infections Management
Canadian institutionsWestern UniversityQueen's UniversityMcGill UniversityUniversity of CalgaryOttawa HospitalUniversity Health NetworkJewish General Hospital
Fundersnot available
KeywordsAssociation (psychology)MedicineBest practiceGeneral surgeryIntensive care medicinePsychologyPolitical sciencePsychotherapist

Abstract

fetched live from OpenAlex

This best practice report provides a brief and comprehensive discussion of studies examining catheter management for impaired bladder emptying in the setting of neurogenic and nonneurogenic lower urinary tract dysfunction. It is based on data obtained from numerous published meta-analyses and original studies identified through literature search using PubMed, Medline, and the Cochrane Library database. The bibliographies of relevant articles were also searched to avoid exclusion of important studies. The following narrative review concentrates on systematic reviews, related guidelines and comparative studies. Articles included in this statement were reviewed using methodology consistent with the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) for evidence synthesis and recommendations. This best practice statement addressed similar subject matter and scope that is of significance to the Canadian urology practice. Competing interest of authors have been considered and addressed.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.636
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.026
GPT teacher head0.257
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2020
Admission routes3
Has abstractyes

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