Clinical evaluation of an automated virtual surgical planning platform for mandibular reconstruction
Bibliographic record
Abstract
BACKGROUND: Virtual surgical planning (VSP), via commercial services or developed in-house, has been applied to facilitate head and neck reconstruction. We evaluate a custom, automated planning software. METHODS: Prospectively, VSP of 25 consecutive patients undergoing segmental mandibular reconstruction was performed. Postoperative CT was used to assess structural accuracy of VSP. Operative time, length of stay, and complication rate of the prospective cohort were compared with those of 25 consecutive retrospective historical cases. RESULTS: The deviations between the plan and execution in mandibular width, projection, and volumetric overlap were 2.32 ± 3.91, 2.39 ± 1.72, and 0.59 ± 0.51 mm respectively. Compared with historical data, there was a significant reduction in operative time and length of stay, and no significant difference in complication rates. CONCLUSION: This is the largest prospective series evaluating an in-house VSP workflow for mandibular reconstruction and the first clinical evaluation of an automated planning platform.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".