3D Exoscope Navigation-Guided Approach to Middle Cranial Fossa
Bibliographic record
Abstract
OBJECTIVE: To test the feasibility and efficacy of a 3D exoscope navigation-guided middle cranial fossa (MCF) approach to the internal auditory canal (IAC); to potentially obviate the need to use dissection landmarks and instead, use the navigation probe as a guide to find structures and drill down to the IAC. PATIENTS: Cadaveric dissection of six temporal bones. INTERVENTION: Computed tomography temporal bone was performed with fiducials on each specimen before the dissection to employ the navigation system. Using a 3D exoscope with navigation by Synaptive (Toronto, Ontario, Canada), the MCF approach was performed. MAIN OUTCOME MEASURES: Navigation accuracy, ability to identify critical structures, and ability to drill out the IAC successfully. RESULTS: All six specimens had the IAC successfully drilled out using the 3D exoscope. All dissections were performed with navigation and did not require dissecting out the greater superficial petrosal nerve and superior semicircular canal. One specimen used landmark dissection to confirm the IAC after navigation had been used to locate the IAC first. Navigation accuracy mean was 1.86 mm (range, 1.56-2.05 mm). CONCLUSION: A 3D exoscope navigation-guided MCF approach to the IAC is feasible without landmark dissection.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".