Development of a Steerable Miniature Instrument to Manage Internal Carotid Artery Injury in Endoscopic Transsphenoidal Surgery Simulation
Bibliographic record
Abstract
Endoscopic transsphenoidal surgery is challenged by restricted visualization and dexterity, and the risk of internal carotid artery (ICA) injury. This study pursued two objectives: Development of a steerable, miniature multi-tool combining visualization and suction/irrigation, and development of a simulation model for ICA injury. The multi-tool featured a two degrees of freedom notched nitinol wrist controlled by a joystick. A theoretical range of motion of 90 degrees was intended. The inner lumen of the wrist was designed for suction and irrigation, a miniature camera attached to the tip would provide visualization. During testing, slack in the actuation cables affected the tools workspace and control. A maximum force of 0.45 N was applied through the tip. The simulation model was manufactured from medical grade ABS. It featured a removable nose cartridge for a cost efficient replacement method. A peristaltic pump and a needle tip were used for ICA injury simulation. For future evaluation of the model, a 5 point Likert scale was developed. Despite successful tests, some limitations remained. The tool was affected by slack and did not include illumination. No mucosal layer was included in the simulation model and haemostasis had to be assessed manually.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".