MétaCan
Menu
← Back to cohort
Record W1942362905 · doi:10.5489/cuaj.625

Measuring up to high standards

2013· article· en· W1942362905 on OpenAlexaffvenueabout
Pierre I. Karakiewicz

Bibliographic record

VenueCanadian Urological Association Journal · 2013
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsDilemmaCurriculumMedicineFamily medicineMedical educationUrologyPsychologyPedagogy

Abstract

fetched live from OpenAlex

The current issue of CUAJ covers a variety of important topics. In the lead article, Nickel and colleagues provide the results of a survey of Canadian urologists about BPH visits as well as the diagnostic and treatment patterns. An average urologist only saw 15 BPH patients weekly, despite the fact that most surveyed (63%) practised in the community. The average initial visit IPSS was 14 and the overwhelming majority of men were treated medically: 44.7%, 17.9% and 11.1%, respectively, received an α-blocker, 5-α reductase or both. A TURP was offered to an additional 5%. The IPSS score and the rate of therapy are elevated. This may imply that urological referrals are predominantly made for symptomatic individuals, where medical therapy is required. The effect of therapy may be implied from the repeat visit IPSS 2-point decrease relative to the initial IPSS. Unfortunately, the relatively low proportion of participants (27 completed surveys v. 86 invited = 31.4%) might be indicative of a participation bias, in which those more familiar and more interested in BPH may have been more likely to participate. Mickelson and MacNeily provide expert insight about the CanMEDS project, which for the past decade has either elated or haunted those at academic institutions. Although some CanMEDS competencies (Medical Expert, Communicator and Scholar) pose no problems in our curricula, others (Collaborator, Manager, Health Advocate and Professionalism) may trigger a conceptual dilemma that might hinder their implementation and subsequent evaluation. These difficulties are compounded by busy academic practices, which leave little time and energy for the CanMEDS competencies, especially the more nebulous ones. Further difficulties stem from the lack of validation and (or) quantification of the benefits of the CanMEDS competencies on the overall health and (or) quality of care. Finally, Dong and colleagues describe their institutional series of 77 consecutive laparoscopic pyeloplasties. The sample size and the quality of outcomes of this series are commendable, and outcomes exceed or at least parallel those from US centres of excellence. The significance of this Canadian report stems from many difficulties that Canadian urologists face in comparison with US urologists, especially for costly and technologically advanced surgical techniques (laparoscopy or robotics). Difficulties with developing Canadian surgical expertise in such fields originate from more limited patient volume relative to the United States as well as to health–economic barriers that dampen the rapid clinical implementation of modern medical technologies in Canada. Canadian laparoscopy and robotics have also clearly been affected by a more restricted patient pool and by the health–economic considerations, which make the achievement of equally successful outcomes substantially more difficult in Canada. Interinstitutional collaborations could circumvent some of the patient volume limitations and should be encouraged throughout the Canadian urological community.

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)0.045
metaresearch head score (Gemma)0.163
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: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.238

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.163
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.007
Science and technology studies0.0050.004
Scholarly communication0.0130.013
Open science0.0030.012
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0210.007

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 head0.052
GPT teacher head0.347
Teacher spread0.295 · 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
GenreCommentary

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

Citations0
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Urological Association Journal→Same topicPrimary Care and Health Outcomes→French-language works237,207→