Influence of Intra-Oral Scanner (I.O.S.) on The Marginal Accuracy of CAD/CAM Single Crowns
Bibliographic record
Abstract
The aim of this in vitro study was to compare the quality of digital workflows generated by different scanners (Intra-oral digital scanners (I.O.S.s)) focusing on marginal fit analysis. A customized chrome-cobalt (Cr-Co) implant abutment simulating a maxillary right first molar was fixed in hemi-maxillary stone model and scanned by eight different I.O.S.s: Omnicam® (Denstply Sirona, Verona, Italy) CS3500®, CS3600®, (Carestream Dental, Atlanta, GA, USA), True Definition Scanner® (3M, St. Paul, MN, USA), DWIO® (Dental Wings, Montreal, Quebec, Canada), PlanScan® (Planmeca Oy, Helsinki, Finland), 3D PROGRESS Plus® (MHT, Verona, Italy), TRIOS 3® (3Shape, Copenhagen, Denmark). Nine scans were performed by each tested I.O.S. and 72 copings were designed using a dental computer-assisted-design/computer-assisted-manufacturing (CAD/CAM) software (exocad GmbH, Darmstadt, Germany). According to CAD data, zirconium dioxide (ZrO2) copings were digitally milled (Roland DWX-50, Irvine, CA, USA). Scanning electron microscope (SEM) direct vision allowed for marginal gap measurements in eight points for each specimen. Descriptive analysis was performed using mean, standard deviation, and median, while the Kruskal–Wallis test was performed to determine whether the marginal discrepancies were significantly different between each group (significance level p < 0.05). The overall mean marginal gap value and standard deviation were 53.45 ± 30.52 μm. The minimum mean value (40.04 ± 18.90 μm) was recorded by PlanScan®, then 3D PROGRESS Plus® (40.20 ± 21.91 μm), True Definition Scanner® (40.82 ± 26.19 μm), CS3500® (54.82 ± 28.86 μm) CS3600® (59,67 ± 28.72 μm), Omnicam® (61.57 ± 38.59 μm), DWIO® (62.49 ± 31.54 μm), while the maximum mean value (67.95 ± 30.41 μm) was recorded by TRIOS 3®. The Kruskal–Wallis tests revealed a statistically significant difference (p-value < 0.5) in the mean marginal gaps between copings produced by 3D PROGRESS Plus®, PlanScan, True Definition Scanner, and the other evaluated I.O.S.s. The use of an I.O.S. for digital impressions may be a viable alternative to analog techniques. Although in this in vitro study PlanScan®, 3D PROGRESS Plus® and True Definition Scanner® may have showed the best performances, all I.O.S.s tested could provide clinically encouraging results especially in terms of marginal accuracy, since mean marginal gap values were all within the clinically acceptable threshold of 120 μm.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".