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Record W2029746157 · doi:10.1002/ase.234

Use of the one‐minute preceptor as a teaching tool in the gross anatomy laboratory

2011· article· en· W2029746157 on OpenAlexaff
Lap Ki Chan, Jeffrey Wiseman

Bibliographic record

VenueAnatomical Sciences Education · 2011
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsMcGill University
Fundersnot available
KeywordsPreceptorGross anatomyTeaching methodMedical educationIdentification (biology)Style (visual arts)AnatomyPsychologyMathematics educationMedicineBiology

Abstract

fetched live from OpenAlex

The one-minute preceptor (OMP) is a time-efficient technique used for teaching in busy clinical settings. It consists of five microskills: (1) get a commitment from the student, (2) probe for supporting evidence, (3) reinforce what was done right, (4) correct errors and fill in omissions, and (5) teach a general rule. It can also be used to address structure-identification questions in gross anatomy laboratory small-group settings. The OMP is an active learner-centered teaching approach that prepares students for a style of learning that they need to master in clinical settings, provides novice anatomy teachers with an efficient and effective teaching strategy, and moves anatomy learning beyond mere name tagging to active knowledge construction.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.633
Threshold uncertainty score0.174

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.027
GPT teacher head0.273
Teacher spread0.246 · 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 designTheoretical or conceptual
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

Citations19
Published2011
Admission routes1
Has abstractyes

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