To what extent can mastication functionality be restored following mandibular reconstruction surgery? A computer modeling approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
STATEMENT OF PROBLEM: Advanced cases of head and neck cancer involving the mandible often require surgical removal of diseased sections and subsequent replacement with donor bone. During the procedure, the surgeon must make decisions regarding which bones or tissues to resect. This requires balancing tradeoffs related to issues such as surgical access and post-operative function; however, the latter is often difficult to predict, especially given that long-term functionality also depends on the impact of post-operative rehabilitation programs. PURPOSE: To assist in surgical decision-making, we present an approach for estimating the effects of reconstruction on key aspects of post-operative mandible function. MATERIAL AND METHODS: We develop dynamic biomechanical models of the reconstructed mandible considering different defect types and validate them using literature data. We use these models to estimate the degree of functionality that might be achieved following post-operative rehabilitation. RESULTS: We find significant potential for restoring mandibular functionality, even in cases involving large defects. This entails an average trajectory error below 2 mm, bite force comparable to a healthy individual, improved condyle mobility, and a muscle activation change capped at a maximum of 20%. CONCLUSION: These results suggest significant potential for adaptability in the masticatory system and improved post-operative rehabilitation, leading to greater restoration of jaw function.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it