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Record W2021531211 · doi:10.1002/ase.1309

A novel patchwork model used in lecture and laboratory to teach the three‐dimensional organization of mesenteries

2012· article· en· W2021531211 on OpenAlexaff
Geoffroy Noël

Bibliographic record

VenueAnatomical Sciences Education · 2012
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsMcGill University
Fundersnot available
KeywordsMesenteriesPeritoneal cavityGross anatomyHuman anatomyDissection (medical)AnatomyMedicineMedical education

Abstract

fetched live from OpenAlex

Anatomy teaching is seeing a decline in both lecture and laboratory hours across many medical schools in North America. New strategies are therefore needed to not only make anatomy teaching more clinically integrated, but also to implement new interactive teaching techniques to help students more efficiently grasp the complex organization of the human body. Among the difficult anatomical concepts that students struggle to understand, the anatomy of the peritoneal cavity with its complex projections of peritoneum could benefit strongly from new learning aids. In this report, an innovative teaching tool is presented to engage students during both lecture and laboratory, and help them build three-dimensional (3D) mental maps of peritoneal cavity. The model consists of a patchwork of mesenteries and gut made from colored cloth stitched together onto a T-shirt to denote the origin and outflow of each peritoneum projection. As the lecturer wears the life-size model, the students can appreciate the 3D organization of the peritoneal cavity on a living body. In addition, the T-shirt model can be used in parallel with dissection to ensure a strong reinforcement of the spatial understanding of the peritoneal cavity.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.503
Threshold uncertainty score0.135

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.248
Teacher spread0.239 · 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

Citations6
Published2012
Admission routes1
Has abstractyes

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