Virtual surgical planning for maxillary reconstruction with the scapular free flap: An evaluation of a simple cutting guide design
Bibliographic record
Abstract
BACKGROUND: The study's objective is to assess the feasibility and utility of VSP for maxillary reconstruction with the scapular free flap. METHODS: An open-source VSP platform was used to create the reconstruction models and simple guides. Clinical, operative, and postoperative data were collected. RESULTS: Ten patients in the VSP cohort and 18 in the non-VSP control cohort were included in the study. There was a significant reduction in operative time (256.0 ± 69.4 vs. 448.1 ± 108.2 min, p < 0.01), tracheotomy rate (20% vs. 72%, p < 0.01), increased two-team utilization rate (80% vs. 0%, p < 0.01) and better reconstructive accuracy (7.5 ± 3.4 vs. 11.7 ± 7.6 mm, p = 0.048) for the VSP cohort. CONCLUSIONS: Maxillary reconstruction planned with an in-house open-source VSP platform and accompanied simple guides can facilitate a two-team approach, reduce operative time, and improve structural accuracy. This open-source technology has great potential to be readily applied in other institutions to improve efficiency and outcomes.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".