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Record W3022595731 · doi:10.5489/cuaj.6667

A Canadian framework for managing prostate cancer during the COVID-19 pandemic: Recommendations from the Canadian Urologic Oncology Group and the Canadian Urological Association

2020· article· en· W3022595731 on OpenAlexaffvenueabout
Andrea Kokorovic, Alan So, Sebastién J. Hotte, Peter C. Black, Brita Danielson, Urban Emmenegger, Antonio Finelli, Tamim Niazi, Frédéric Pouliot, Bobby Shayegan, Srikala S. Sridhar, Éric Vigneault, Andrew Loblaw, Ricardo Rendon

Bibliographic record

VenueCanadian Urological Association Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsMcGill UniversityPrincess Margaret Cancer CentreDalhousie UniversityUniversity Health NetworkUniversity of TorontoUniversité LavalUniversity of AlbertaMcMaster UniversitySunnybrook Health Science CentreJuravinski Cancer CentreUniversity of British Columbia
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Prostate cancerMedicine2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)OncologyProstateInternal medicineFamily medicineCancerVirologyOutbreakDisease

Abstract

fetched live from OpenAlex

triaging and the use of systemic therapies in genitourinary malignancies 7,9 .The purpose of this publication is to provide a multidisciplinary framework focused on prostate cancer management in the setting of the COVID-19 global pandemic within the Canadian context. General principles1.This consensus statement is a guide to help physicians manage prostate cancer during

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)0.028
metaresearch head score (Gemma)0.054
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: Methods · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.840

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.054
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0060.006
Science and technology studies0.0230.012
Scholarly communication0.0140.007
Open science0.0080.014
Research integrity0.0150.027
Insufficient payload (model declined to judge)0.0090.002

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.

Opus teacher head0.071
GPT teacher head0.355
Teacher spread0.284 · 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
GenreMethods

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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