Accuracy of a novel prototype dynamic computer‐assisted surgery system
Bibliographic record
Abstract
OBJECTIVES: To implement and evaluate the accuracy of a prototype dynamic computer-assisted surgery (CAS) system for implant osteotomy preparation and compare its accuracy vs. three commercial static CAS systems and the use of an acrylic stent. MATERIAL AND METHODS: Eight osteotomies were prepared in radiopaque partially edentulous mandible and maxilla typodonts. After cone-beam CT acquisition, DICOM files were imported into a prototype dynamic, and three static CAS systems (NobelClinician, Simplant, and CoDiagnostiX). Implant placements were planned to replicate the existing osteotomies and respective guides were requisitioned, along with one laboratory-made acrylic guide. The eight osteotomies per jaw were transferred to one typodont pair mounted in a manikin in a clinical setting and the process was repeated for four additional pairs. The 80 (two jaws × eight holes × five pairs) osteotomies were filled with radiopaque cement in-between the testing series. Three clinicians experienced with the use of the static CAS softwares used in this study prepared each 400 (80 holes × five modalities) osteotomies. One clinician repeated the experiment twice, resulting in a total of 2000 (five clinicians × 400) osteotomies. The lateral, vertical, total, and angular deviations of the actual vs. the original osteotomies in the master typodonts were measured using stereo optical tracking cameras. Linear regression statistics using generalized estimating equations were used for comparisons between the five modalities and omnibus chi-square tests applied to assess statistical significance of differences. RESULTS: The prototype dynamic CAS system was as accurate as other implant surgery planning and transfer modalities. The dynamic and static CAS systems provide superior accuracy vs. a laboratory-made acrylic guide, except vertically. Both dynamic and static CAS systems show on average <2 mm and 5 degrees error. Large deviations between planned and actual osteotomies were occasionally observed, which needs to be considered in clinical practice. CONCLUSIONS: The prototype dynamic CAS system was comparably accurate to static CAS systems.
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How this classification was reachedexpand
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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".