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Record W4292185176 · doi:10.1177/08465371221105532

Canadian Association of Radiologists Prostate MRI White Paper

2022· article· en· W4292185176 on OpenAlexaffabout
Silvia D. Chang, Caroline Reinhold, Iain D. C. Kirkpatrick, Sharon E. Clarke, Nicola Schieda, Casey Hurrell, Derek W. Cool, Adam S. Tunis, Abdullah Alabousi, Brendan Diederichs, Masoom A. Haider

Bibliographic record

VenueCanadian Association of Radiologists Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsMcMaster UniversityWestern UniversityUniversity of TorontoDalhousie UniversitySt. Boniface HospitalNorth York General HospitalMcGill University Health CentreUniversity Health NetworkOttawa HospitalSt. Joseph’s Healthcare HamiltonUniversity of ManitobaMount Sinai HospitalUniversity of CalgaryVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineContext (archaeology)Quality assuranceProstate cancerWhite paperHealth careMedical physicsProstateMalignancyProstate biopsyRadiologyCancerPathologyInternal medicine

Abstract

fetched live from OpenAlex

Prostate cancer is the most common malignancy and the third most common cause of death in Canadian men. In light of evolving diagnostic pathways for prostate cancer and the increased use of MRI, which now includes its use in men prior to biopsy, the Canadian Association of Radiologists established a Prostate MRI Working Group to produce a white paper to provide recommendations on establishing and maintaining a Prostate MRI Programme in the context of the Canadian healthcare system. The recommendations, which are based on available scientific evidence and/or expert consensus, are intended to maintain quality in image acquisition, interpretation, reporting and targeted biopsy to ensure optimal patient care. The paper covers technique, reporting, quality assurance and targeted biopsy considerations and includes appendices detailing suggested reporting templates, quality assessment tools and sample image acquisition protocols relevant to the Canadian healthcare context.

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)0.011
metaresearch head score (Gemma)0.061
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: Other
Teacher disagreement score0.982
Threshold uncertainty score0.992

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.061
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.007
Science and technology studies0.0050.003
Scholarly communication0.0070.002
Open science0.0040.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.1050.051

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 head0.010
GPT teacher head0.241
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; 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

Citations6
Published2022
Admission routes2
Has abstractyes

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Same venueCanadian Association of Radiologists JournalSame topicProstate Cancer Diagnosis and TreatmentFrench-language works237,207