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1. Direct restorative for Class I, II, III, IV, and V cavities
2. Fissure sealant
3. Sealing hypersensitive areas
4. Repair of (in)direct aesthetic restorations, temporary crown & bridge, defect margins when margins are in enamel
5. Blocking out undercuts
6. Liner or base
7. Core build-up
8. Adhesive cementation of ceramic and composite veneers, inlays and onlays with a thickness (

G-ænial Universal Injectable II is a light-cured, nano-filled radiopaque composite resin filled in syringe. The device is used for the restoration of both anterior and posterior teeth, core build-up, adhesive cementation of ceramic and composite veneer, inlays and onlays, and build-up for transparent removable orthodontic retainers. The device is available in 9 shades.

This document is an FDA 510(k) clearance letter for a dental resin material, G-ænial Universal Injectable II. It is important to note that this is NOT an AI/ML medical device submission. Therefore, the information provided in the document focuses on the material's physical and chemical properties and biocompatibility, as compared to predicate dental materials.

The request asks for information typically found in submissions for AI/ML medical devices, such as acceptance criteria based on diagnostic performance metrics (e.g., sensitivity, specificity, AUC), details about test and training sets, expert consensus for ground truth, MRMC studies, and effect sizes of AI assistance. Since this is a dental material, these types of studies are not relevant and are not present in the provided document.

Therefore, the following response will adapt the requested sections to the context of this dental material, explaining what information is available and what is not, given the nature of the device.

Acceptance Criteria and Device Performance for G-ænial Universal Injectable II

The acceptance criteria for G-ænial Universal Injectable II are based on established ISO standards for dental materials and FDA guidance for composite resin devices. The "study that proves the device meets the acceptance criteria" refers to the Performance Bench Tests and Non-Clinical Performance Testing detailed in Section 7 and 8 of the 510(k) summary. These tests assess the physical, chemical, and biological properties of the material.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are generally "Complies" with specific quantitative or qualitative thresholds defined by the standards (e.g., ISO 4049, ISO 6874). The document reports that the device Complies with all listed requirements.

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

For a dental material, the "test set" refers to the samples of the material manufactured and subjected to the performance bench tests and biocompatibility assessments.

• Sample Size: The document does not specify the exact number of samples (e.g., number of specimens for flexural strength, number of animals for biocompatibility tests). It simply states that "Performance testing includes" and "A biocompatibility assessment was completed."
• Data Provenance: The data provenance is internal to the manufacturer (GC America, Inc.) and derived from laboratory testing of the material according to international ISO standards and FDA guidance documents. There is no indication of "country of origin of the data" in the sense of patient data, nor is it a retrospective or prospective study in the clinical trial sense. These are laboratory-based material characterization tests.

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

This question is not applicable to a dental material submission. The "ground truth" for material properties is established by the standardized test methods themselves (e.g., ISO 4049 defines how depth of cure is measured). There are no "experts" establishing ground truth in the sense of clinical interpretations or diagnoses. The expertise lies in adhering to the established test protocols and analyzing results accurately by qualified laboratory personnel.

4. Adjudication Method for the Test Set

This concept is not applicable for dental material performance testing. Adjudication methods (like 2+1, 3+1 consensus) are used in studies involving human interpretation of images or clinical outcomes, typically for AI/ML device validation. Here, tests are quantitative measurements of physical/chemical properties or biological responses.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, and Effect Size of Human Readers Improving with AI vs Without AI Assistance

This question is not applicable. G-ænial Universal Injectable II is a dental restorative material, not an AI-assisted diagnostic or therapeutic device. There are no "human readers" involved in interpreting its performance, nor does it assist human readers. Therefore, no MRMC study was performed, and no effect size on human reader improvement with AI assistance can be reported.

6. If a Standalone (i.e., Algorithm Only Without Human-in-the-Loop Performance) was Done

This question is not applicable. G-ænial Universal Injectable II is a physical dental material, not an algorithm. There is no "standalone performance" of an algorithm. Its performance is measured directly through laboratory tests of its inherent material properties.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

For dental materials, the "ground truth" is based on:

• Standardized Test Methods: Adherence to established ISO standards (e.g., ISO 4049, ISO 6874, ISO 10993) defines the "truth" for material properties like flexural strength, depth of cure, water sorption, and biocompatibility.
• Predicate Device Comparison: Performance is also evaluated in comparison to predicate devices, where "equivalence" often serves as a benchmark for acceptance.

There is no "expert consensus," "pathology," or "outcomes data" in the sense of human diagnostic performance or clinical trial results, as this is a pre-market notification for a material.

8. The Sample Size for the Training Set

This question is not applicable. There is no "training set" for a dental material in the context of machine learning. The material itself is manufactured, and specific properties are tested for quality control and regulatory submission.

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

This question is not applicable, as there is no training set.

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