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Record W1558660544 · doi:10.1002/ase.1487

Development of an interactive anatomical three‐dimensional eye model

2014· article· en· W1558660544 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 institutionsWestern University
Fundersnot available
KeywordsComputer sciencePsychologyHuman–computer interaction

Abstract

fetched live from OpenAlex

The discrete anatomy of the eye's intricate oculomotor system is conceptually difficult for novice students to grasp. This is problematic given that this group of muscles represents one of the most common sites of clinical intervention in the treatment of ocular motility disorders and other eye disorders. This project was designed to develop a digital, interactive, three-dimensional (3D) model of the muscles and cranial nerves of the oculomotor system. Development of the 3D model utilized data from the Visible Human Project (VHP) dataset that was refined using multiple forms of 3D software. The model was then paired with a virtual user interface in order to create a novel 3D learning tool for the human oculomotor system. Development of the virtual eye model was done while attempting to adhere to the principles of cognitive load theory (CLT) and the reduction of extraneous load in particular. The detailed approach, digital tools employed, and the CLT guidelines are described herein.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.288
Teacher spread0.277 · 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