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Take 1 Advanced Rigid Tray is an addition-cure vinyl polysiloxane dental impression material that is used for all crown and bridge, edentulous, orthodontic and implant impression techniques.

The device is an addition-cure vinyl polysiloxane dental impression material that is used for all crowns and bridges, edentulous, orthodontic and implant impression techniques. Take 1 Advanced Rigid Tray is a two-part, base/catalyst – paste/paste system. The product is available in a heavy body viscosity, offered in cartridge 1:1 delivery and Volume 5:1 delivery, and in 3 setting speeds: regular set, fast set and super fast set.

The provided text describes a 510(k) submission for a dental impression material, Take 1 Advanced Rigid Tray. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study of a device's performance against specific acceptance criteria in the way an AI/ML device study would. Therefore, most of the requested information regarding acceptance criteria, sample sizes for test/training sets, expert qualifications, and adjudication methods is not directly applicable or available in the provided text for a device like this.

However, I can extract the information that is present and indicate where it's not applicable.

Here's a breakdown based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

For this specific device, the "acceptance criteria" are implied by demonstrating substantial equivalence to its predicate for certain material properties, rather than explicit numerical thresholds the device must achieve independently. The reported performance is comparative.

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

• Sample Size: Not explicitly stated for specific tests (e.g., how many samples for compressive strength were tested). The text mentions "data from bench testing," implying multiple tests were performed.
• Data Provenance: Bench testing data. No geographic origin is specified, but it was performed by Sybron Dental Specialties, Inc. (USA-based company). Retrospective.

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 dental impression material. The "ground truth" for its performance is derived from physical and chemical measurements rather than expert human interpretation.

4. Adjudication method for the test set

• Not Applicable. As per point 3, no human adjudication was involved in establishing performance metrics for this material.

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

• No. This is not an AI/ML device, nor does it involve human readers. Clinical testing was explicitly stated as not conducted.

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

• Not Applicable. This is a physical dental material; there's no algorithm.

7. The type of ground truth used

• For physical/chemical properties (Working Time, Setting Time, Compressive Strength, etc.): Objective physical and chemical measurements governed by established testing standards (e.g., those specified in ISO standards for dental materials, though specific standard numbers for each test are not listed other than ISO 10993 for biocompatibility).
• For biocompatibility: Adherence to ISO 10993 standards for biological evaluation of medical devices.

8. The sample size for the training set

• Not Applicable. This is not an AI/ML device; there is no training set in the machine learning sense. The "training" in manufacturing would relate to process control and quality assurance, not data-driven model training.

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

• Not Applicable. See point 8.

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Take 1 Advanced Rigid Tray is an addition-cure vinyl polysiloxane dental impression material that is used for all crown and bridge, edentulous, orthodontic and implant impression techniques.

The device is an addition-cure vinyl polysiloxane dental impression material that is used for all crowns and bridges, edentulous, orthodontic and impression techniques. Take 1 Advanced Rigid Tray is a two-part, base/catalyst – paste/paste system. The product is available in a heavy body viscosity, offered in cartridge 1:1 delivery and Volume 5:1 delivery, and in 3 setting speeds: regular set, fast set and super fast set.

This submission pertains to a dental impression material, which is a low-risk device. As a result, the provided documentation focuses on establishing substantial equivalence to a predicate device rather than presenting a detailed study with acceptance criteria and performance data in the context of AI/software. There is no mention of a study involving artificial intelligence, human readers, or specific quantitative performance metrics beyond the general characteristics expected of dental impression materials.

Therefore, many of the requested sections (e.g., sample size for test set, number of experts, MRMC study, standalone performance) are not applicable to the provided information.

However, based on the context of a 510(k) submission for a non-AI device, we can infer some general "acceptance criteria" through the lens of substantial equivalence and device characteristics for dental impression materials.

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a non-AI device, the "acceptance criteria" are implicitly derived from the characteristics of the predicate device and the general intended use of dental impression materials. Performance is reported through the substantial equivalence claim.

Notes on "Acceptance Criteria" for this device:

• No quantitative statistical thresholds are explicitly stated because this is a Class II dental impression material cleared via substantial equivalence, not a high-risk device with specific performance endpoints like sensitivity/specificity for disease detection.
• The "acceptance criteria" here refer to matching the material composition, physical properties (viscosity, setting times), and intended use to a legally marketed predicate device.

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

Not applicable. The document does not describe a "test set" in the context of evaluating a software algorithm or diagnostic device. The evaluation for substantial equivalence typically involves material characterization and comparison to the predicate, not a clinical study with a specified test set of patient data.

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

Not applicable. This is not a study requiring expert-established ground truth for a test set of medical cases.

4. Adjudication Method for the Test Set

Not applicable. No test set requiring adjudication is mentioned.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study is typically conducted for diagnostic imaging devices or AI-powered interpretation systems to evaluate the impact of the AI on human reader performance, which is not relevant for a dental impression material.

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

Not applicable. This is a physical dental impression material, not an algorithm, so the concept of "standalone performance" for an algorithm is not relevant.

7. The Type of Ground Truth Used

Not applicable in the conventional sense of expert consensus, pathology, or outcomes data for diagnostic accuracy. For this type of device, the "ground truth" for demonstrating equivalence would be based on established dental material standards and performance data for the predicate device, as well as the physical and chemical properties of the new device confirming it performs as intended.

8. The Sample Size for the Training Set

No training set is mentioned or applicable. This is a physical product, not a machine learning model.

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

Not applicable, as there is no training set for a machine learning model.

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