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Record W2744635650 · doi:10.1007/s13187-017-1259-7

Development and Implementation of a Continuing Medical Education Program in Canada: Knowledge Translation for Renal Cell Carcinoma (KT4RCC)

2017· article· en· W2744635650 on OpenAlexaffabout
Luke T. Lavallée, Ryan Fitzpatrick, Lori Wood, Joan Basiuk, Christopher Knee, Sonya Cnossen, Ranjeeta Mallick, Kelsey Witiuk, Marie Vanhuyse, Simon Tanguay, Antonio Finelli, Michael A.S. Jewett, Naveen S. Basappa, Jean‐Baptiste Lattouf, Geoffrey Gotto, Sohaib Al-Asaaed, Georg A. Bjarnason, Ronald B. Moore, Scott North, Christina Canil, Frédéric Pouliot, Denis Soulières, Vincent Castonguay, Wassim Kassouf, Ilias Cagiannos, Christopher Morash, Rodney H. Breau

Bibliographic record

VenueJournal of Cancer Education · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsCentre hospitalier universitaire de QuébecSunnybrook Health Science CentreMemorial University of NewfoundlandUniversité LavalCentre Hospitalier de l’Université de MontréalUniversity of OttawaMcGill UniversityUniversité de MontréalUniversity of AlbertaQueen Elizabeth II Health Sciences CentreUniversity of TorontoDalhousie UniversityOttawa HospitalUniversity Health NetworkUniversity of CalgaryPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineContinuing medical educationSpecialtyTest (biology)Family medicineMultidisciplinary approachRenal cell carcinomaKidney diseaseContinuing educationInternal medicineMedical education

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.235
GPT teacher head0.515
Teacher spread0.280 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2017
Admission routes2
Has abstractno

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