Development of augmented reality training simulator systems for neurosurgery using model-driven software engineering
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.
Bibliographic record
Abstract
Neurosurgical procedures are complicated processes, providing challenges and demands ranging from medical knowledge and judgment to the neurosurgeons dexterity and perceptual capacities. Deliberate training of common neurosurgical procedures and underlying tasks is extremely important. One effective method for the training is to enhance the required surgical training tasks through the use of neurosurgical simulators. Development of neurosurgical simulators is challenging due to many reasons. In this work, we proposed to facilitate the development of new augmented reality neurosurgical simulator systems through the adoption of model-driven engineering. Our developed systems involve the interactive visualization of three-dimension brain meshes in order to train users and simulate a targeting task towards a variety of predetermined virtual targets. We present our results in a way which highlights two new design artifacts through our MDE approach.
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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 | 0.001 | 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 it