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Record W2623785479 · doi:10.3138/jvme.0716-122r1

Use of a Garment as an Alternative to Body Painting in Equine Musculoskeletal Anatomy Teaching

2017· article· en· W2623785479 on OpenAlexvenueno aff
Mariana M. Sattin, Vickitoriana K.A. Silva, Rafael Magdanelo Leandro, R. P. P. Foz Filho, Mauricio M. De Silvio

Bibliographic record

VenueJournal of Veterinary Medical Education · 2017
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsnot available
Fundersnot available
KeywordsClothingPalpationPaintingHuman anatomyPopularityAnatomyHuman bodyMedicineMedical educationVisual artsArtPsychologySurgery

Abstract

fetched live from OpenAlex

Living anatomy is gaining increasing popularity as an alternative to the use of preserved cadaver specimens in musculoskeletal anatomy teaching. This article describes the development of a garment painted with musculoskeletal structures as an alternative to body painting. Garments offer some advantages over traditional body painting in anatomy teaching. The technique can be used across different disciplines, enhances students' ability to identify anatomic structures in living bodies, and provides insights into the topography of one or more body systems at the same time. The fact that garments are amenable to palpation by large groups of students with no damage to the painting favors repeated use in hands-on wet labs. Garments such as the one described in this article introduce a novel approach to interdisciplinary teaching and learning, which can be combined with traditional anatomy teaching methods. The first garment produced depicts part of the equine musculoskeletal system. Steps in garment construction are highlighted and indications, advantages, and limitations of the method discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.045
GPT teacher head0.405
Teacher spread0.360 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2017
Admission routes1
Has abstractyes

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