The First Alveolar Bone Graft Simulator
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
Alveolar bone graft (ABG) surgery in cleft patients is technically challenging. The procedure requires design, dissection and release of soft tissue flaps to create a seal around the bone graft. In addition, visualization during the procedure is challenging within the confines of the cleft. These features make ABG surgery difficult to learn and teach, and it is, therefore, a suitable procedure for the use of a simulator. A high-fidelity cleft ABG simulator was developed using three-dimensional printing, polymer, and adhesive techniques. Simulated ABG surgery was performed by two expert cleft surgeons for a total of five simulation sessions to test the simulator's features and the ability to perform the critical steps of an ABG. ABG surgery was successfully performed on the simulator. The simulations involved interacting with realistic dissection planes as well as multi-layered synthetic soft (periosteum, mucosa, gingiva, adipose tissue) and hard (teeth, bone) tissue. The simulator allowed performance of cleft marginal incisions, dissection, and elevation of a muco-gingival-periosteal flap, creation of nasal upturned and palatal downturned flaps, nasal and palatal side closure, insertion of simulated bone graft material, and advancement of the muco-gingival-periosteal flap for closure of the anterior wall of the cleft. The ABG simulator allowed performance of the critical steps of ABG surgery. This is the first ABG simulator developed, which incorporates the features necessary to practice the procedure from start to finish.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 0.004 |
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