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Dental casting alloy used in combination with dental ceramics for fabrication of metallo-ceramic restoration.

Medium gold casting alloy

This document is a 510(k) premarket notification for a dental casting alloy, AUREBOND 51. The information provided is primarily focused on demonstrating substantial equivalence to a predicate device, Jelenko Olympia, rather than presenting a study proving the device meets specific performance acceptance criteria for an AI/ML medical device.

Therefore, most of the requested information regarding acceptance criteria, study design for AI/ML performance, sample sizes, expert involvement, and ground truth establishment is not present in this document. This typically applies to AI/ML software as a medical device (SaMD) or as part of a medical device (SiMD).

Here's an attempt to answer the questions based only on the provided text, recognizing its limitations for the requested context:

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

Based on the document, the "acceptance criteria" are implied to be the ranges and values of the predicate device (Jelenko Olympia) for its composition and physical/mechanical properties. The "reported device performance" are the measured values for the new device (Aurebond 51).

Conclusion from the document: "Essentially similar composition, only slight difference in mechanical properties." This indicates that the observed differences were deemed acceptable for substantial equivalence.

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

• Sample Size: Not specified. Standard material testing would use multiple samples, but the exact number isn't in the provided text.
• Data Provenance: The device manufacturer (Aurex) is in the Republic of South Africa. The testing methods applied are "as in ANSI/ADA 5 and ISO 9693," which are international standards for dental materials. The raw data origin (country, retrospective/prospective) is not specified.

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)

This is not applicable to a material testing submission. "Ground truth" in this context would be physical and chemical measurements performed according to established standards, not expert consensus or interpretation.

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

Not applicable. Material testing follows standardized methods, not expert adjudication.

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

Not applicable. This is a material science submission, not an AI/ML diagnostic device.

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

Not applicable. This is a material science submission, not an AI/ML diagnostic device.

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

The "ground truth" for this device's performance is established by standardized physical and chemical testing methods using laboratory equipment, as referenced by ANSI/ADA 5 and ISO 9693 standards. It's not based on expert consensus, pathology, or outcomes data in the way an AI/ML diagnostic would be.

8. The sample size for the training set

Not applicable. This is a material science submission, not an AI/ML device that requires a training set.

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

Not applicable. This is a material science submission, not an AI/ML device.

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