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Record W4300470483 · doi:10.17615/4398-b918

Incorporating CanMEDS and subspecialty training into paediatric residency programs: Why are we still deficient?

2020· article· en· W4300470483 on OpenAlexaboutno aff
Andrew Ni, Gautam Kumar, Sarah Lawrence, Asif Doja

Bibliographic record

VenueUNC Libraries · 2020
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsSubspecialtyResidency trainingTraining (meteorology)Medical educationMedicineFamily medicineGeographyContinuing education

Abstract

fetched live from OpenAlex

The Royal College of Physician and Surgeons of Canada mandates that paediatric training programs in Canada incorporate subspecialty training and the teaching and evaluation of the seven CanMEDS roles into their curriculum. The literature suggests that newly practicing paediatricians feel inadequately prepared in many subspecialties and CanMEDS roles.

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)0.029
metaresearch head score (Gemma)0.085
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: Commentary
Teacher disagreement score0.268
Threshold uncertainty score0.532

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.085
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0070.008
Scholarly communication0.0100.014
Open science0.0030.009
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0200.004

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 head0.122
GPT teacher head0.360
Teacher spread0.238 · 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
Published2020
Admission routes1
Has abstractyes

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