Development of a Virtual da Vinci Xi Training Simulator for Robotic In-Utero Open Spina Bifida Repair
Bibliographic record
Abstract
Open spina bifida (OSB), also known as myelomeningocele, is a neural tube defect where the spine of a developing fetus is exposed. Repair of the defect before birth improves outcomes for both mother and child. A novel minimally invasive robotic in-utero approach is proposed, requiring new tools to enable surgeon planning and training. This work presents a dynamic virtual simulator of the da Vinci Xi Robotic Surgical System with an interactive fetal environment that allows surgeons to practice simulated OSB repair. The simulator is built in the Asynchronous Multi-Body Framework (AMBF) and integrated with the da Vinci Research Kit (dVRK). The directional and rotational control mappings were consistent with the respective controls tested on a real operative da Vinci Xi robot (R2 ≥ 0.979). Kinematics were further validated with path tracing tasks which yielded similar trajectory deviation errors between the simulator and the real Xi robot. Surgeons completed a suturing task using the simulator and evaluated the performance, agreeing that simulator robot controls are realistic, fetal model and suturing are somewhat realistic, and that the simulator is useful as a training tool. This simulator has potential applications in research, surgical training and preoperative planning for robotic approaches to fetal surgical procedures.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".