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Record W7100040767

Development and Evaluation of a Mandatory Course in Geriatric Medicine for Fourth Year Medical Students

2014· article· en· W7100040767 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicThallium and Germanium Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeriatricsMedical schoolEducational measurementPopulationPopulation ageingCore Knowledge
DOInot available

Abstract

fetched live from OpenAlex

Background and Objectives: As the population ages, older adults will make up an increasing proportion of the practices of most physicians. Because of this, education of medical students in Geriatric Medicine is essential, yet there is considerable variability in the amount, timing within the curriculum, and content of geriatric training in Medical Schools. Our goal was to develop and evaluate an integrated, mandatory 3-week geriatric medicine course for fourth year medical students with emphasis on knowledge acquisition. Methods: All fourth year medical students at Dalhousie Medical School underwent 2 days of didactic teaching on core geriatric topics and a 2-week clinical rotation. Pre-rotation knowledge testing occurred on the first day of the rotation. On the final examination, students were retested on the 15 pre-rotation questions, as well as 5 additional questions that they had not encountered previously. Results: There was a statistically significant improvement in examination performance from 46.9 % on the pretest to 78.6 % on the final examination (t=24.7, p<.001). It is unlikely that the significant improvement in scores is simply a result of repeat testing, as students tended to score better on the five additional questions that they had not seen before.

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 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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0010.000

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 head0.021
GPT teacher head0.319
Teacher spread0.298 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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