A Mixed Reality Technology as a Supplemental Learning Tool of the Cardiovascular System
Bibliographic record
Abstract
Learning anatomy and physiology is a difficult task for students entering the field of Health Sciences and Medicine. While cadavers and textbooks are the current standard for teaching anatomy, potential alternative is the utilization of mixed reality technologies. These technologies have the ability to augment human anatomy models directly onto the user, who can then interact with them in a 3D envi-ronment. Our proposed technology, known as the Magic Mir-ror, was assessed in the Anatomy and Physiology I lecture at the University of Ottawa. Data from surveys was collected based on a five-point Likert Scale. Surveys focused on student interaction with the Magic Mirror technology as well as their thoughts about how it compared to learning the cardiovascular system versus traditional Atlas textbooks. Final results demon-strated a strong positive assessment of the Magic Mirror which offers the potential to continue improving the technology for future implementation in anatomy curricula.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".