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Record W1978840140 · doi:10.1503/cjs.027713

Enhancing medical students’ education and careers in global surgery

2014· article· en· W1978840140 on OpenAlexaffvenue
Alexandre Gosselin-Tardif, Guillaume Butler‐Laporte, Melina C. Vassiliou, Kosar Khwaja, Georges Ntakiyiruta, Patrick Kyamanywa, Tarek Razek, Dan Deckelbaum

Bibliographic record

VenueCanadian Journal of Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsMedicineMedical education

Abstract

fetched live from OpenAlex

With surgical conditions being significant contributors to the global burden of disease, efforts aimed at increasing future practitioners' understanding, interest and participation in global surgery must be expanded. Unfortunately, despite the increasing popularity of global health among medical students, possibilities for exposure and involvement during medical school remain limited. By evaluating student participation in the 2011 Bethune Round Table, we explored the role that global surgery conferences can play in enhancing this neglected component of undergraduate medical education. Study results indicate high rates of student dissatisfaction with current global health teaching and opportunities, along with high indices of conference satisfaction and knowledge gain, suggesting that global health conferences can serve as important adjuncts to undergraduate medical education.

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)0.004
metaresearch head score (Gemma)0.012
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.001
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.017
GPT teacher head0.298
Teacher spread0.281 · 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
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

Citations25
Published2014
Admission routes2
Has abstractyes

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