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A dual-cure, composite resin core build-up material that is usually used to restore missing tooth structure for which a dental restoration, usually a crown, is fabricated.

A dual-cure, composite resin, core build-up material that is usually used to restore missing tooth structure for which a dental restoration, usually a crown, is fabricated. It is substantially equivalent to many predicate materials that include self-, light-, and dual-cure types. This material incorporates fluoride-containing (trace amounts) glass filler particles. No Bisphenol-A or its precursors are used in the manufacturing process. The material is supplied in light-safe dual-barrel cartridges.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Parkell, Inc. Absolute Dentin II device:

Based on the provided 510(k) summary (K132115) for Absolute Dentin II, this document pertains to a dental material, specifically a composite resin core build-up material, and not an AI/ML-driven medical device. Therefore, many of the requested categories related to AI/ML device studies (like sample sizes for test/training sets, experts for ground truth, adjudication methods, MRMC studies, or standalone algorithm performance) are not applicable to this submission.

The "acceptance criteria" for this type of device are primarily based on demonstrating substantial equivalence to predicate devices through biocompatibility testing and non-clinical performance testing of mechanical properties.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria (as demonstrated by testing) and Reported Device Performance:

Since this is a material rather than a diagnostic or therapeutic AI device, "acceptance criteria" are typically defined by meeting established ISO standards for biocompatibility and demonstrating comparable physical properties to predicate devices. The document lists the tests conducted and states that all tests were passed.

2. Sample size used for the test set and the data provenance:

• Sample size: Not specified. Standard biocompatibility tests and material property tests typically use a predefined number of samples as per the relevant ISO or ASTM standards, but the exact count is not given in this summary.
• Data provenance: Not explicitly stated but assumed to be from laboratory testing as per the ISO standards mentioned.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not Applicable. This is a material testing conformity rather than a diagnostic device requiring expert interpretation of results for ground truth. Biocompatibility and mechanical property tests have objective readouts.

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

• Not Applicable. Adjudication methods are relevant for subjective interpretations, which are not involved in these types of material tests.

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 not an AI-driven device.

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

• Not Applicable. This is not an AI-driven device.

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

• For biocompatibility: Ground truth is established by the specific, objective criteria defined within each ISO standard (e.g., cell viability percentages, absence of specific reactions).
• For non-clinical performance (mechanical properties): Ground truth is established by physical measurement against established material science parameters and comparison to predicate device performance.

8. The sample size for the training set:

• Not Applicable. This is not an AI/ML device, so there is no training set in the context of machine learning.

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

• Not Applicable. As above, no training set for an AI/ML model.

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