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Pro-V Coat is indicated for use as a separating agent when placed between any resin based material and to the substrate to which permanent bonding is not desired, such as:

1. any resin based material to the adhesive layer.
2. any resin based material to the remaining tooth structure.

Pro-V Coat is a water soluble separating agent that effectively prohibits bonding of the resin-based material used for temporary restorations to the adhesive interface or to the remaining tooth structure. Pro-V Coat along with the temporary restoration will remain in place for a certain period of time. The temporary restorative material is easily removed with hand instruments and the Pro-V Coat is rinsed off with copious amounts of water. Pro-V Coat is designed to clean up effortlessly without any residue. Pro-V Coat will not compromise subsequent adhesion of the final restoration.

The provided document is a 510(k) summary for a dental separating agent, Pro-V Coat. It describes the device, its indications for use, and a comparison to a predicate device to demonstrate substantial equivalence. However, it does not include the detailed information requested in the prompt regarding acceptance criteria, a specific study proving it meets those criteria, sample sizes for test and training sets, expert qualifications, or ground truth establishment relevant to AI/ML device evaluation.

The document's performance data section focuses on physical/mechanical properties and biocompatibility as a comparison to the predicate device, not on specific acceptance criteria for an AI/ML diagnostic or predictive tool.

Therefore, the following information cannot be extracted from the provided text:

1. A table of acceptance criteria and the reported device performance: No specific acceptance criteria are defined for performance metrics in a table format. The performance data section vaguely states that "Pro-V Coat was an effective separating agent and that it inhibited bonding between the adhesive / tooth structure and the restorative material," but no quantitative metrics or targets are given.
2. Sample sizes used for the test set and the data provenance: No test set is mentioned, as this is not an AI/ML device evaluation.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable.
4. Adjudication method for the test set: Not applicable.
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, as this is not an AI-assisted device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable, as there's no diagnostic or predictive ground truth involved.
8. The sample size for the training set: Not applicable.
9. How the ground truth for the training set was established: Not applicable.

The document describes material properties and chemical composition comparisons, along with biocompatibility testing (ISO 10993-1) to demonstrate safety. The "performance data" refers to general R&D testing protocols to show effectiveness in separating materials, not a specific study with defined acceptance criteria typical for an AI/ML medical device.

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