Assessing Bimanual Performance in Brain Tumor Resection With NeuroTouch, a Virtual Reality Simulator
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
BACKGROUND: Validated procedures to objectively measure neurosurgical bimanual psychomotor skills are unavailable. The NeuroTouch simulator provides metrics to determine bimanual performance, but validation is essential before implementation of this platform into neurosurgical training, assessment, and curriculum development. OBJECTIVE: To develop, evaluate, and validate neurosurgical bimanual performance metrics for resection of simulated brain tumors with NeuroTouch. METHODS: Bimanual resection of 8 simulated brain tumors with differing color, stiffness, and border complexity was evaluated. Metrics assessed included blood loss, tumor percentage resected, total simulated normal brain volume removed, total tip path lengths, maximum and sum of forces used by instruments, efficiency index, ultrasonic aspirator path length index, coordination index, and ultrasonic aspirator bimanual forces ratio. Six neurosurgeons and 12 residents (6 senior and 6 junior) were evaluated. RESULTS: Increasing tumor complexity impaired resident bimanual performance significantly more than neurosurgeons. Operating on black vs glioma-colored tumors resulted in significantly higher blood loss and lower tumor percentage, whereas altering tactile cues from hard to soft decreased resident tumor resection. Regardless of tumor complexity, significant differences were found between neurosurgeons, senior residents, and junior residents in efficiency index and ultrasonic aspirator path length index. Ultrasonic aspirator bimanual force ratio outlined significant differences between senior and junior residents, whereas coordination index demonstrated significant differences between junior residents and neurosurgeons. CONCLUSION: The NeuroTouch platform incorporating the simulated scenarios and metrics used differentiates novice from expert neurosurgical performance, demonstrating NeuroTouch face, content, and construct validity and the possibility of developing brain tumor resection proficiency performance benchmarks.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it