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Record W2285399374 · doi:10.5489/cuaj.3583

Recommendations for the improvement of bladder cancer quality of care in Canada: A consensus document reviewed and endorsed by Bladder Cancer Canada (BCC), Canadian Urologic Oncology Group (CUOG), and Canadian Urological Association (CUA), December 2015

2016· article· en· W2285399374 on OpenAlexaffvenueabout
Wassim Kassouf, Armen Aprikian, Peter C. Black, Girish S. Kulkarni, Jonathan I. Izawa, Libni Eapen, Adrian Fairey, Alan So, Scott North, Ricardo Rendon, Srikala S. Sridhar, Tarik Alam, Fadi Brimo, Normand Blais, Chris Booth, Joseph L. Chin, Peter Chung, Darrel Drachenberg, Yves Fradet, Michael A.S. Jewett, Ronald B. Moore, Christopher Morash, Bobby Shayegan, Geoffrey Gotto, Neil Fleshner, Fred Saad, D. Robert Siemens

Bibliographic record

VenueCanadian Urological Association Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsMcMaster UniversityUniversité LavalUniversity of ManitobaQueen's UniversityUniversité de MontréalUniversity of AlbertaMcGill University Health CentreUniversity of OttawaUniversity of TorontoWestern UniversityDawson CollegeUniversity of CalgaryPrincess Margaret Cancer CentreDalhousie UniversityUniversity Health NetworkUniversity of British Columbia
Fundersnot available
KeywordsMedicineBladder cancerFamily medicineGenitourinary systemMultidisciplinary approachCancerMEDLINEGynecologyInternal medicine

Abstract

fetched live from OpenAlex

This initiative was undertaken in response to concerns regarding the variation in management and in outcomes of patients with bladder cancer throughout centres and geographical areas in Canada. Population-based data have also revealed that real-life survival is lower than expected based on data from clinical trials and/or academic centres. To address these perceived shortcomings and attempt to streamline and unify treatment approaches to bladder cancer in Canada, a multidisciplinary panel of expert clinicians was convened last fall for a two-day working group consensus meeting. The panelists included urologic oncologists, medical oncologists, radiation oncologists, patient representatives, a genitourinary pathologist, and an enterostomal therapy nurse. The following recommendations and summaries of supporting evidence represent the results of the presentations, debates, and discussions. Methodology

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.023
GPT teacher head0.301
Teacher spread0.278 · 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; a candidate call from one teacher head, not a consensus.

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

Citations55
Published2016
Admission routes3
Has abstractyes

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