Visualization of anterior skull base defects with intraoperative cone‐beam CT
Bibliographic record
Abstract
BACKGROUND: The role of cone-beam CT (CBCT) in demonstrating anterior skull base defects (ASBDs), differing in size and location, was investigated. The study was designed to describe the potential advantage of CBCT in the setting of an intraoperative cerebrospinal fluid (CSF) leak. METHODS: In all, 120 ASBD were evaluated in 5 cadaver heads. Orthogonal and oblique slices were reconstructed. Observer studies assessed the visibility of ASBD in each location as a function of defect size. RESULTS: For 1-, 2-, and 4-mm defects, the percentage that were undetectable ranged from 20% to 33%, 0% to 14%, and 0% to 5%, respectively. Confident breach detection increased with defect size and was most challenging in the lateral lamella and cribriform. CBCT permitted confident detection of ASBD as small as about 2 mm in the fovea ethmoidalis and planum. Oblique views were found to be superior to orthogonal planes. CONCLUSIONS: The ability to identify ASBD depended on the size and location of defect. Oblique viewing planes were optimal for ASBD visualization.
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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 | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".