A comparison of the accuracy of fit of 2 methods for fabricating implant-prosthodontic frameworks.
Bibliographic record
Abstract
PURPOSE: To compare the in vitro 3-dimensional (3D) accuracy of fit of laser-scanned Computer Numeric Controlled (CNC)-milled implant titanium frameworks to that of conventional cast frameworks. MATERIALS AND METHODS: Nine cast frameworks were fabricated on the mandibular master casts of 9 patients with 5 implants each following the well-established conventional fabrication technique. The frameworks were then laser scanned, and 9 CNC-milled titanium frameworks matching the outline of the conventional frameworks were fabricated. The accuracy of fit of both framework types was measured using a contact-type coordinate measuring machine and a computer program developed specifically for this purpose. Statistical analysis was done by a series of paired ttests. RESULTS: The laser-scanned CNC-milled frameworks showed significantly less distortion along the x-axis (transversal, d(x)) compared with the conventional frameworks (means: 33.7 microm and 49.2 microm, respectively) (P = .011). The titanium frameworks also demonstrated significantly less distortion on the horizontal plane compared with the conventional frameworks (means: 56 microm and 85 microm, respectively) (P = .012). The d(y) (sagittal) and d(z) (vertical) axes and total 3D distortion (square root of dx(2) + dy(2) + dz(2)) showed less distortion overall in the laser-scanned CNC-milled frameworks, but this was not statistically significant (mean: 22.3 vs 35.6 microm, 13.3 vs 59.2 microm, 51 vs 114.1 microm, respectively, for y, z, and 3D distortion). CONCLUSION: Within the limitations of this study, fabrication of an implant-prosthodontic framework using the CNC milling technique yields a more accurate fit than the currently used cast technique. In vivo studies are needed to investigate the clinical significance of this recorded difference.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".