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Record W2113453129 · doi:10.1080/0142159021000063925

Computer-assisted instruction of carpal bone radiograph interpretation

2002· article· en· W2113453129 on OpenAlexaff
Matthew W. Westendorp, Robert McGraw

Bibliographic record

VenueMedical Teacher · 2002
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineObjective structured clinical examinationRadiographyPhysical therapyMedical educationMedical physicsCarpal bonesRadiology

Abstract

fetched live from OpenAlex

This paper describes the development of a computer-assisted self-directed learning module to teach carpal bone radiograph interpretation to clinical clerks, and the evaluation of its efficacy as a teaching tool. The module was developed using commercially available authoring software and in collaboration with radiologists. Following an eight-month period where the module was a mandatory component of the clerkship rotation in emergency medicine, a convenience sample of 36 volunteers from various levels of medical training were recruited, and their ability to interpret carpal radiographs was tested in an objective structured clinical examination (OSCE). The scores of the clinical clerks who had completed the module were shown to be similar to the scores of emergency medicine residents with specific experience and training in this skill (mean: 5 vs. 6), and different from the scores of trainees who had not completed the module and had no specific training in this skill (mean: 5 vs. 2). This study suggests that our module may be an effective tool in teaching this skill to clinical clerks.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.925
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.019
GPT teacher head0.295
Teacher spread0.276 · 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 designOther design
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

Citations7
Published2002
Admission routes1
Has abstractyes

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