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Record W4210806897 · doi:10.5489/cuaj.7763

Canadian Urological Association guideline: Management of small renal masses – Full-text

2022· article· en· W4210806897 on OpenAlexaffvenueabout
Patrick O. Richard, Philippe D. Violette, Bimal Bhindi, Rodney H. Breau, Wassim Kassouf, Luke T. Lavallée, Michael A.S. Jewett, John R. Kachura, Anil Kapoor, Maxine Noel-Lamy, Michael Ordon, Stephen E Pautler, Frédéric Pouliot, Alan So, Ricardo Rendon, Simon Tanguay, Christine A. Collins, Maryam Kandi, Bobby Shayegan, Andrew E. Weller, Antonio Finelli

Bibliographic record

VenueCanadian Urological Association Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsBC Cancer AgencyCentre hospitalier universitaire de QuébecSt. Michael's HospitalSt. Joseph’s Healthcare HamiltonUniversity of CalgaryPrincess Margaret Cancer CentreMcMaster UniversityMcGill University Health CentreUniversity of OttawaWestern UniversityUniversity of TorontoCapital District Health AuthorityUniversity Health NetworkHamilton Health SciencesKidney Foundation of CanadaCentre Hospitalier Universitaire de Sherbrooke
Fundersnot available
KeywordsGuidelineAssociation (psychology)MedicineUrologyPsychologyPathology

Abstract

fetched live from OpenAlex

of recommendations1. Patients diagnosed with SRM should undergo routine laboratory investigations, including at a minimum a serum creatinine and glomerular filtration rate (Clinical principle).2. Patients with SRM incidentally discovered on routine imaging should be investigated with a multiphasic, contrast-enhanced abdominal computed tomography (CT) or magnetic resonance imaging (MRI) scan (Clinical principle).3.For patients with suspected renal malignancy, a baseline chest X-ray is suggested to assess for pulmonary metastases (Conditional recommendation, low certainty in evidence of effects).4. Patients with SRM and pre-existing renal dysfunction in whom a radical nephrectomy is being considered, may be offered renal scintigraphy when the result may alter their management (Clinical principle). 5. Patients with SRM should be offered a renal mass biopsy when the result of the biopsy may alter their management (Adopted from Kidney Cancer Research Network of Canada [KCRNC] consensus on the role of

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.293
Threshold uncertainty score0.583

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0040.001
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0220.013

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 head0.019
GPT teacher head0.231
Teacher spread0.211 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations47
Published2022
Admission routes3
Has abstractyes

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