MétaCan
Menu
Back to cohort
Record W6959644471 · doi:10.11575/prism/45628

Infectious Diseases Training in Canada: One Size Does Not Fit All

2001· other· en· W6959644471 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2001
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Mapping and Diversity in Plants and Animals
Canadian institutionsnot available
Fundersnot available
KeywordsTraining (meteorology)Scale (ratio)Infectious disease (medical specialty)Public healthMEDLINEProgram evaluation

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate training in infectious diseases, determining which components of the training program best prepare residents for their career choices and where improvements are needed.METHOD: A cross-sectional survey was mailed to all 14 physicians who had graduated from both the Adult and Paediatric Infectious Diseases Training Program at the University of Calgary from 1985 to 1998. Responses about the adequacy of training were measured using a Likert-type scale and a qualitative questionnaire.RESULTS: Of 14 mailed questionnaires, nine responses were received (64%). Two-thirds of respondents were in an academic setting, and seven (78%) graduates obtained postfellowship training. The specialists in academic settings were all engaged in multiple nonclinical activities. The clinical and diagnostic microbiological components of training received the highest scores in terms of adequacy of training.CONCLUSION: Graduates of the University of Calgary training program indicated an overall satisfaction with their training. However, improvements are needed in career counselling, health administration, antibiotic utilization, infection prevention and specialized outpatient clinics. Potential strategies for addressing these issues include didactic lectures, enhanced exposure to clinical outpatient settings and provision of designated faculty mentors.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.205
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
GPT teacher head0.182
Teacher spread0.171 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueUniversity of CalgarySame topicGenetic Mapping and Diversity in Plants and AnimalsFrench-language works237,207