Accuracy of a Digital Impression System Based on Active Wavefront Sampling Technology for Implants Considering Operator Experience, Implant Angulation, and Depth
Bibliographic record
Abstract
BACKGROUND: There is a scarce knowledge on the accuracy of intraoral digital impression systems for dental implants. PURPOSE: The purpose of this study is to evaluate the accuracy of a digital impression system considering clinical parameters. MATERIALS AND METHODS: A master model with six implants (27, 25, 22, 12, 15, 17) was fitted with polyether ether ketone scan bodies. Implant no. 25 was placed with 30° mesial angulation in relation to the vertical plane (y axis), and implant no. 15 was positioned with 30° distal angulation. Implant no. 22 was placed 2 mm and no. 12, 4 mm below the gingiva. Experienced (n = 2) and inexperienced operators (n = 2) performed scanning (Lava Chairside Oral Scanner; 3 M ESPE, St Paul, MN, USA) at standard and high accuracy mode. Measurements involved five distances (27-25, 27-22, 27-12, 27-15, 27-17). Measurements with high accuracy three-dimensional coordinated measuring machine (CMM) of the master model acted as the true values. The data obtained were subtracted from those of the CMM values. RESULTS: Experience of the operator significantly influenced the results (p = .000). Angulation (p = .195) and depth of implant (p = .399) did not show significant deviation from the true values. The mean difference between standard and high accuracy mode was 90 μm. CONCLUSIONS: With the active wavefront sampling, technology-based digital impression system training seems to be compulsory. Impressions of angulated implants may diminish the accuracy of the impression, yet the results were not significant.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".