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Record W2037481269 · doi:10.1080/01421590601032450

From the facts to the screen: a blended model of teaching basic hospital skills to 2nd year medical students

2006· article· en· W2037481269 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedical Teacher · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicProblem and Project Based Learning
Canadian institutionsMcGill University
Fundersnot available
KeywordsTUTORMedical educationPsychologyComputer scienceMedicineMathematics education

Abstract

fetched live from OpenAlex

We report an interactive course design which simulated the clinical setting for practicing basic hospital skills. The two-part course included (1) instructor-led, Flash-based interactive lectures; and (2) web-based case using interactive hospital forms. Our program evaluation showed that integrated sessions complemented with web-based interactive cases and hospital forms offered a better student preparation for the Geriatric Medicine clerkship and improved tutor perceptions of student performance during early rotations in the academic year. From the facts to the screen: a blended model of teaching basic hospital skills to 2nd year medical studentsAll authorsGustavo Duque MD, Ayanna Roberts, Joanne Hui, Nancy Posel, David Fleiszer & Wendy Chiuhttps://doi.org/10.1080/01421590601032450Published online:03 July 2009Table Download CSVDisplay Table

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.

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)0.007
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.005
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 science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.324
Teacher spread0.310 · 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