In Vitro Measurements of Precision of Fit of Implant‐Supported Frameworks. A Comparison between “Virtual” and “Physical” Assessments of Fit Using Two Different Techniques of Measurements
Bibliographic record
Abstract
BACKGROUND: Comparisons between different techniques measuring fit of implant-supported frameworks are few. PURPOSE: The purpose of this study was to compare data on precision of fit from two highly accurate measuring techniques and, also, to compare results using software programs for fit assessments considering both a "virtual" as well as a "physical" (i.e., more clinical) situation. MATERIALS AND METHODS: Five computer numerical control-milled titanium frameworks (Procera Implant Bridge, Nobel Biocare AB, Göteborg, Sweden) were fabricated from individual model/pattern measurements, simulating a clinical situation. Measurements of fit between frameworks and models were performed by means of a coordinate measuring machine (CMM; Zeiss Prismo Vast, Carl Zeiss Industrielle Messtechnik GmbH, Oberkochen, Germany) linked to a computer and an optical, high-resolution, three-dimensional scanner (Atos 4M SO, GOM International AG, Widen, Switzerland). Collected data on distortions between frameworks and models were analyzed and compared between the two measurement techniques. A comparison between "virtual" and "physical" fit assessments was also performed, based on data from the three-dimensional scanner. RESULTS: When using "virtual" fit assessment programs, overall mean three-dimensional distortion between implant and framework center points in absolute figures was 37 (SD 22) and 14 µm (SD 8) for the CMM and three-dimensional scanning measurements, respectively. Corresponding mean three-dimensional distortion when using a "physical" fit assessment program in the scanner was 43 µm (SD 24) (p < 0.001). Mean horizontal (x-axis) measurements of the distance between the two terminal implants of the models and the frameworks were 33.772 and 33.834 mm for the CMM technique. Corresponding measurements for the three-dimensional scanner was 33.798 and 33.806 mm, respectively. Horizontal distances from the three-dimensional scanner were, for most measurements, greater than for the CMM measurements. CONCLUSION: Measurements of fit between frameworks and models may vary depending on what technique is used and how fit assessments regarding "virtual" or "physical" fit is approached.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".