The <scp>3D</scp> ‐Robotic Exoscope Compared With the Microscope in Cochlear Implant and Translabyrinthine Surgery
Bibliographic record
Abstract
OBJECTIVES: The three-dimensional (3D) exoscope is an innovative viewing platform in microsurgery with the potential of offering improved ergonomics and surgical performance. This study systematically evaluated the ergonomic characteristics, visualization, and subjective performance of an exoscope system compared to the microscope in cochlear implantation (CI) and translabyrinthine resection of vestibular schwannomas (VS). METHODS: This prospective qualitative study was performed at a tertiary referral center. Ergonomics were evaluated subjectively with questionnaires in addition to the Rapid Upper Limb Assessment Tool (RULA), which was used as a quantitative measure of ergonomic risk. Performance and visualization parameters were assessed at specific surgical milestones in comparing the exoscope to the microscope. RESULTS: Ergonomically, exoscopic surgery led to less straining in both subjective (p < 0.001) and objective (p < 0.001) measures. Visualization in terms of expansiveness, visual clarity, and depth was superior at each surgical milestone in VS (exoscope n = 7; microscope n = 5) and most of the CI milestones (exoscope n = 24; microscope n = 22). CI surgeries were completed faster with the exoscope (p = 0.007). CONCLUSION: The 3D-exoscope afforded clear ergonomic advantages as compared with the microscope in so far as to reduce strains and potentially long-term risks to surgeons. Additional advantages over the traditional surgical microscope included improvement in the field of view and visual clarity, with no effect on time to completion. Further advancements in exoscope technology will ease the adaptation of this innovative device in cochlear implant and translabyrinthe surgeries.
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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 | 0.004 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".