Endoscopic Anatomy of the Orbital Floor and Maxillary Sinus
Bibliographic record
Abstract
Endoscopic repair of orbital blow-out fractures could become a predictable and efficient treatment alternative to traditional methods. However, maxillary sinus endoscopy provides a complex and disorienting view of the orbital floor. To be a useful and consistent technique for providing access to the orbital floor, specific knowledge of maxillary endoscopic anatomy is required. The purpose of the study was to provide an anatomic description of the orbital floor via the endoscopic approach. Objectives include defining consistent landmarks for use in endoscopic repair of orbital floor fractures. Using 0- and 30-degree rigid endoscopes, 6 fresh cadavers (12 maxillary sinuses) were examined via a standard Caldwell-Luc approach. Computed tomographic scans, plastic molds, and digital images were used to compare observable averages within bony anatomy. Potential bony landmarks were correlated with soft-tissue anatomy in fresh specimens. The maxillary ostium, orbital floor, and lateral ethmoid air cells were visualized, and their structures were described. Observations were made in relation to the anatomy of the orbital floor and maxillary sinus, including fracture pattern and force transmission pathways. An "orbitomaxillary" sinus bony thickening was identified and described for the first time. This study provides the basis for further refinement of surgical technique and opens the door for future clinical trials using endoscopic repair.
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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 | 0.000 |
| 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) | 0.002 | 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".