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Record W1526103333 · doi:10.1002/ase.1445

The cranial nerve skywalk: A 3D tutorial of cranial nerves in a virtual platform

2014· article· en· W1526103333 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

VenueAnatomical Sciences Education · 2014
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsUniversity of Manitoba
FundersDivision of Materials ResearchUniversity of KentuckyBrown University
KeywordsCranial nervesGross anatomyDissection (medical)CraniofacialAnatomyComputer scienceVisualizationMedicineArtificial intelligence

Abstract

fetched live from OpenAlex

Visualization of the complex courses of the cranial nerves by students in the health-related professions is challenging through either diagrams in books or plastic models in the gross laboratory. Furthermore, dissection of the cranial nerves in the gross laboratory is an extremely meticulous task. Teaching and learning the cranial nerve pathways is difficult using two-dimensional (2D) illustrations alone. Three-dimensional (3D) models aid the teacher in describing intricate and complex anatomical structures and help students visualize them. The study of the cranial nerves can be supplemented with 3D, which permits the students to fully visualize their distribution within the craniofacial complex. This article describes the construction and usage of a virtual anatomy platform in Second Life™, which contains 3D models of the cranial nerves III, V, VII, and IX. The Cranial Nerve Skywalk features select cranial nerves and the associated autonomic pathways in an immersive online environment. This teaching supplement was introduced to groups of pre-healthcare professional students in gross anatomy courses at both institutions and student feedback is included.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.623
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.006
GPT teacher head0.243
Teacher spread0.237 · 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