Preclinical Performance Evaluation of a Robotic Endoscope for Non-Contact Laser Surgery
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
Despite great efforts, transoral robotic laser surgery has not been established clinically. Patient benefits are yet to be proven to accept shortcomings of robotic systems. In particular, laryngeal reachability and transition from microscope to accurate endoscopic laser ablation have not been achieved. We have addressed those challenges with a highly integrated robotic endoscope for non-contact endolaryngeal laser surgery. The current performance status has been assessed in multi-level user studies. In addition, the system was deployed to an ex vivo porcine larynx. The robotic design comprises an extensible continuum manipulator with multifunctional tip. The latter features laser optics, stereo vision, and illumination. Vision-based performance assessment is derived from depth estimation and scene tracking. Novices and experts (n = 20) conducted teleoperated delineation tasks to mimic laser ablation of delicate anatomy. Delineation with motion-compensated and raw endoscopic visualisation was carried out on planar and non-planar nominal patterns. Root mean square tracing errors of less than 0.75 mm were feasible with task completion times below 45 s. Relevant anatomy in the porcine larynx was exposed successfully. Accuracy and usability of the integrated platform bear potential for dexterous laser manipulation in clinical settings. Cadaver and in vivo animal studies may translate ex vivo findings.
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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 | 0.000 |
| 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 it