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Record W2160982315

Cultivating interest in family medicine: family medicine interest group reaches undergraduate medical students.

2007· article· en· W2160982315 on OpenAlexaffabout
Nora McKee, Meredith McKague, Vivian R. Ramsden, Raenelle E. Poole

Bibliographic record

VenuePubMed · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsInterest groupMedical educationJournal clubFamily medicineMedicinePrimary careAlternative medicineSpecial Interest GroupClubComputer sciencePathology
DOInot available

Abstract

fetched live from OpenAlex

PROBLEM ADDRESSED: Fewer medical students are choosing careers in family medicine across Canada. One way to cultivate student interest is through creation of family medicine interest groups. Students, residents, community-based family physicians, and academic faculty can all contribute to the success of such groups. OBJECTIVE OF PROGRAM: A family medicine interest group provides information about the challenging and rewarding career of family medicine through medical students' exposure to family physicians and residents. PROGRAM DESCRIPTION: A group of faculty and undergraduate students combined forces to form the Family Medicine Club. Development of this group and results of evaluation of its effectiveness to date are discussed. CONCLUSION: One mechanism to increase interest in primary care as a career is to initiate and foster a family medicine interest group that links students with family physicians.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0240.003

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 head0.163
GPT teacher head0.356
Teacher spread0.193 · 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 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

Citations34
Published2007
Admission routes2
Has abstractyes

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