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ZENO® Al cco Discs are milling blanks from which single copings and primary components for anteriors and premolars can be made. These are intended for use as ceramic frameworks for dental prosthetics.

ZENO Al eco Discs are milling blanks composed of pure aluminium oxide. They are intended to be used by professional dental technicians for making single copings and primary components for anteriors and premolars to apply them as ceramic frameworks for dental prosthetics for the sole use of particular patients. ZENO Al eco Discs can be machined in all machines of the ZENO Tec system. The manufacturing process of this ceramic framework consists of different steps. At first the model has to be scanned. In the next step, the restoration has to be designed virtually with the help of the CAD technology. Thereafter, the realization of this design has to be carried out by the CAM technology. In a final step after hard sintering of the ZENO Al eco, the framework can be veneered with a suitable veneering ceramic.

This document is a 510(k) summary for the ZENO Al eco Disc, a dental milling blank. This type of submission focuses on demonstrating substantial equivalence to a predicate device rather than conducting a full clinical trial with acceptance criteria for a new AI/software device. Therefore, many of the requested categories related to AI performance studies are not applicable or cannot be extracted from this document.

Here's an analysis of the provided text in relation to your request:

1. A table of acceptance criteria and the reported device performance

This document does not specify quantitative acceptance criteria or device performance data in the way an AI/software device submission would. Instead, it relies on demonstrating equivalence to a predicate device based on material properties and intended use.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

N/A. This is a material-based dental device, not an AI/software device requiring a test set of data for performance evaluation. The submission relies on laboratory testing of material properties, not a "test set" of patient data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

N/A. Not applicable to this type of device submission. Ground truth, in the context of AI, involves expert-level annotations or diagnoses, which is not relevant here.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

N/A. Not applicable to this type of device submission.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

N/A. This is not an AI-powered device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

N/A. This is not an AI-powered device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

For a material-based device like this, "ground truth" typically refers to established standards for material properties (e.g., strength, biocompatibility) as assessed through standardized laboratory tests. The document implies that these properties were tested and found to be comparable to the predicate device, but specific details of these tests are not provided in the summary.

8. The sample size for the training set

N/A. This is not an AI/machine learning device. The "training" for such a device would involve optimizing the manufacturing process to achieve desired material properties, not training an algorithm on a dataset.

9. How the ground truth for the training set was established

N/A. Not applicable to this type of device submission.

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