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Light curing one-component opaquer to mask framework structures. Signum opaque F is the opaquer component for veneering materials and denture base materials (heat/cold curing denture acrylics) offered by Kulzer.

Signum opaque F is a light-curing, one component opaquer used for extraoral color-masking of framework structures for crowns, bridges, and/or partial dentures. The veneering composites are processed by dental restoration by veneering framework-supported restorations, such as metal or zirconia frameworks.

Signum opaque F is a paste stored in a syringe featuring a plunger and a closing cap. The product is dispensed and is then applied with a disposable brush until the scaffolding frame is completely covered. After polymerization, the crown or bridge is inserted into the oral cavity, adapted and connected to the remaining residual teeth or functionally adapted.

The provided text describes the 510(k) premarket notification for a dental device called "Signum opaque F." However, it does not contain information about the acceptance criteria or the study that proves the device meets those criteria in the context of an AI/ML-driven medical device.

The document is a traditional 510(k) submission for a non-AI dental material (tooth shade resin material). It focuses on:

• Substantial Equivalence: Comparing the new device (Signum opaque F) to a legally marketed predicate device (VITA VM LC FLOW) in terms of indications for use, technological characteristics, and conformance to standards.
• Mechanical and Thermal Testing: Mentioning that these tests were performed (shear bond strength, shelf-life at differing temperatures) but without providing specific acceptance criteria or detailed results.
• No Clinical Study for Performance: Stating that a clinical investigation "is not necessary and the route for this clinical evaluation is literature based" because the product type (veneering composites) is "well-established."

Therefore, I cannot populate the table or answer the specific questions related to AI/ML device performance, test sets, ground truth establishment, expert adjudication, or MRMC studies, as this information is not present in the provided text.

The request's parameters (AI/ML context, ground truth, experts, MRMC, etc.) are generally relevant to submissions for AI/ML-enabled medical devices, which leverage algorithms that interpret or process medical data. The provided document concerns a dental material's physical and chemical properties and its intended use, not an AI's diagnostic or predictive performance.

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