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Record W7037086676

Design and implementation of the 2012 Canadian shoulder course for senior orthopedic residents

2016· article· en· W7037086676 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicColeoptera Taxonomy and Distribution
Canadian institutionsnot available
Fundersnot available
KeywordsOrthopedic surgeryCourse evaluationTest (biology)Course (navigation)Duration (music)Multiple choice
DOInot available

Abstract

fetched live from OpenAlex

© 2016 Background The objective of the present paper is to analyze the first edition of a comprehensive shoulder course for senior orthopedic surgery residents and the chosen evaluation tools. Hypothesis A course focusing on shoulder surgery, requested by graduating residents in orthopedic surgery, will have a strong level of satisfaction and help improve skills, knowledge, and problem solving abilities in this domain as measured by a pre and post-test. Material and methods A two-day course was created with practical sessions, lectures, and case studies. Participants were given a multiple choice pre and post course test and evaluation questionnaires after each session. Results Sixty residents attended the course. Nine of the fifteen sessions scored above the 90% satisfaction cut-off; none of the sessions scored below 80%. However, only one question showed a statistically significant improvement after the course. Discussion Response to this course was overwhelmingly positive and the sessions received positive evaluations. However, the method to evaluate residents was not adequate; residents reported learning on their freeform evaluations but this was not represented on the multiple choice evaluation method. Evaluation tools and course duration will be modified in future iterations to improve assessment and teaching. Level of evidence IV. Study design Observational.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.569

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.081
GPT teacher head0.302
Teacher spread0.221 · 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
Published2016
Admission routes1
Has abstractyes

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