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ESTENIA C&B is indicated for the following applications for the restoring crowns and defects.

1. Facing cast crowns and facing cast bridges
2. Jacket crowns
3. Inlays and onlays
4. Bridges with frameworks

This device is a polymer based material, used for fabricating prosthetic appliance such as facing cast crowns, facing cast bridges, jacket crowns, inlays, onlays or bridges with frameworks, and for repair of those prosthetic appliances made of resin based crown and bridge materials or porcelain.

The provided text does not contain detailed information about acceptance criteria or a specific study proving the device meets them in the way typically found for an AI/ML medical device. This document is a 510(k) summary for a dental material (ESTENIA C&B), which relies on substantial equivalence to predicate devices rather than a performance study against specific acceptance criteria for AI algorithms.

Here's an analysis based on the provided text, addressing the points where information is available and noting where it is not:

1. Table of Acceptance Criteria and Reported Device Performance

Not applicable in the context of an AI/ML device. This document describes a dental material and its physical/mechanical properties, not an AI algorithm's performance against clinical endpoints.

The document states:

• "The physical and mechanical properties of ESTENIA C&B are verified by evaluation test based on ISO 10477."

This suggests that compliance with ISO 10477 serves as the "acceptance criteria" for the physical and mechanical properties of the material. However, no specific numerical values or ranges are provided for these properties, nor are the reported results from the evaluation test detailed.

2. Sample Size Used for the Test Set and Data Provenance

Not applicable for an AI/ML device. This document refers to the evaluation of a dental material. The "test set" would likely refer to samples of the material tested in a lab for physical and mechanical properties. No details on the sample size or data provenance (e.g., country of origin, retrospective/prospective) for these material tests are provided.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications

Not applicable. The ground truth for a dental material's physical and mechanical properties is typically established by standardized laboratory testing methods, not by expert consensus in a clinical setting.

4. Adjudication Method

Not applicable. Adjudication methods (e.g., 2+1, 3+1) are for resolving discrepancies in expert interpretations of clinical data, which is not the context here.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

Not applicable. MRMC studies are specific to evaluating AI's impact on human reader performance, which doesn't apply to a dental material.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Study Was Done

Not applicable. This is not an AI algorithm. The performance described relates to the intrinsic physical and mechanical properties of the dental material.

7. The Type of Ground Truth Used

The ground truth for the device's properties is based on standardized laboratory testing methods, specifically those outlined in ISO 10477. In this context, "ground truth" refers to the objectively measured physical and mechanical properties of the material according to established international standards.

8. The Sample Size for the Training Set

Not applicable. This is not an AI/ML device, so there is no concept of a "training set" in the machine learning sense. The material itself is "trained" through its manufacturing process to achieve certain properties.

9. How the Ground Truth for the Training Set Was Established

Not applicable. As noted above, this isn't an AI/ML device. The "ground truth" for the material's properties is established through the ISO 10477 evaluation tests during development and quality control of the manufacturing process.

In summary, the provided 510(k) summary for ESTENIA C&B pertains to a dental material and relies on demonstrating substantial equivalence to predicate devices, primarily through chemical composition and physical/mechanical properties verified against an international standard (ISO 10477). It does not contain the type of AI/ML device performance study details requested.

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