Endoscopic Repair of Orbital Floor Fractures: Computed Tomographic Analysis Using a Cadaveric Model
Bibliographic record
Abstract
OBJECTIVE: To determine the efficiency (and accuracy) of endoscopic repair versus transconjunctival repair for orbital floor fractures in a cadaveric model. METHODS: In nine fresh cadavers, a standardized technique created orbital floor fractures. One orbit was repaired using an endoscopic transantral approach, whereas the other was repaired using a standard transconjunctival approach. Commercially available implants were used for floor reconstruction. A validated computed tomographic volumetric analysis of the orbits was performed at three time points: prefracture, postfracture, and postrepair. Student's t-test analyzed the percentage of volume change in the prefracture and postrepair stages for each approach. RESULTS: The percentage of change between the prefracture and postrepair states was not statistically significant for transconjunctival (p = .834) or endoscopic (p = .366) repair. The average differences between transconjunctival repair and endoscopic repair were not statistically significant (p = .732). CONCLUSIONS: This study objectively confirms the efficiency of the endoscopic repair of orbital floor fractures when compared with traditional techniques in the cadaveric model.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".