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1. Class I, II, III, IV and V restorations
2. Root surface restoration
3. Core build-up

EQUIA LC ONE is a resin-modified glass ionomer dental restorative material which is intended to be used as a restorative filling material for direct restorations and or core buildups. The applicant device is provided as a powder/liquid formulation in a mixing capsule.

N/A

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1. Cementation of all types of all ceramic, resin and metal-based inlays, onlays, crowns and bridges.
2. Cementation of metal, ceramic, fiber posts, and cast post and cores.
3. Cementation of all ceramic and composite veneers.
4. Final cementation of crowns and bridges on implant abutments.

G-CEM ONE is a dual-cured self-adhesive resin cement with a tooth primer, G-CEM ONE ADHESIVE ENHANCING PRIMER. The mixed cement hardens through polymerization. The adhesive component is an acidic monomer which also can polymerize with frame-forming monomers. This copolymerizing reaction provides higher physical strength than resin-modified glass ionomer cements. Using the primer on the prepared tooth, surface modification and cement polymerization are promoted and hardened along with the cement. The cement syringe consists of Paste A and B, which are filled in a one-body/two chamber syringe. Both pastes are automixed with a mixing tip and applied directly to restorations or prepared cavity.

I am sorry, but the provided text is a 510(k) premarket notification for a dental cement (G-CEM ONE) and does not contain information about an AI/ML device.

Therefore, I cannot extract the acceptance criteria or study details regarding AI performance as requested in your prompt. The document focuses on the physical and chemical properties of the dental cement and its biocompatibility, comparing it to predicate dental cements.

Specifically, the document includes:

• Acceptance Criteria and Reported Device Performance (for the dental cement): This is presented in the tables under "9. Performance Bench Tests" for G-CEM ONE and "G-CEM ONE ADHESIVE ENHANCING PRIMER" on pages 4 and 5. These criteria relate to properties like film thickness, working time, setting time, flexural strength, water sorption, solubility, radiopacity, appearance, coatability, color tone, and refractive index.
• Sample Size for Test Set and Data Provenance: Not specified for any AI/ML context. The performance tests are laboratory bench tests, not clinical studies with human subjects.
• Number of Experts and Qualifications: Not applicable as it's not an AI/ML device requiring expert ground truth for interpretation.
• Adjudication Method: Not applicable.
• Multi Reader Multi Case (MRMC) Comparative Effectiveness Study: Not mentioned as it's not an AI/ML device.
• Standalone Performance: Not applicable for an AI/ML device.
• Type of Ground Truth Used: Not applicable for an AI/ML device.
• Sample Size for Training Set & How Ground Truth for Training Set Was Established: Not applicable as it's not an AI/ML device.

Please provide a document related to an AI/ML device if you wish for me to extract information on its acceptance criteria and study data.

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BZF-29 is a two component (PRIMER and ADHESIVE), light-cured bonding agent suitable for:

• Bonding of light cured composites and acid modified composites (compomers) to tooth structure.
• Bonding of dual cured luting and core build up composites to tooth structure as long as these materials are light cured.
• Intraoral repairs of porcelain fused to metal crowns and composite veneer crowns with metal backing.
• . Intraoral repairs of all ceramic crowns (except zirconia and alumina), hybrid resin jacket crowns, CAD/CAM hybrid resin crowns and composites.
• . Intraoral repairs of porcelain fused to zirconia crowns, porcelain fused to alumina crowns and full zirconia crowns.
• . Treatment of hypersensitive teeth.

BZF-29 is a two component, light-cured bonding agent to bond light-cured composite resins to tooth structure, composites, hybrid ceramics, ceramics and metal surfaces, and for the treatment of hypersensitive teeth.

The provided document is a 510(k) premarket notification for a dental bonding agent, BZF-29, seeking substantial equivalence to a predicate device, G-Premio BOND. The document details performance bench tests and comparisons to establish this equivalency, but it does not describe a study involving human subjects or AI assistance. Instead, the "performance" described refers to material properties and bond strengths as mechanical measures.

Therefore, many of the requested criteria regarding human readers, AI assistance, ground truth establishment methods for training, and detailed study specifics are not applicable or cannot be extracted from this document, as it focuses on demonstrating product characteristics through bench and biocompatibility testing against a predicate device.

Here's an analysis of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

Notes on the Table:

• For "Appearance," "Curing property," "Application characteristics," "Color," "pH," and "Refraction index," the document states that the applicant device complies with all the requirements of 1AB-1500-3-10706 (Company specification) and then lists the specific requirements. The predicate device's performance against these specific criteria is not individually detailed but is implied to be "Conformed" for overall comparison purposes to establish substantial equivalence.
• The acceptance criteria for bond strength are stated as ">10MPa" for all categories.

2. Sample size used for the test set and the data provenance
The document does not explicitly state the sample size (number of teeth/samples tested) for each specific bench test (e.g., bond strength measurements). It refers to the results as statistical averages with standard deviations, implying multiple samples were used for each measurement.
The data provenance is not specified beyond "bench tests" conducted by the manufacturer, presumably in a laboratory setting. There is no information on country of origin or whether it was retrospective or prospective, as these terms are typically used for clinical studies involving patients, which is not the case here.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This is not applicable. The "ground truth" for the test set is established by objective physical and chemical measurements (e.g., MPa for bond strength, pH values, visual checks for homogeneity, SEM for dentin tubules) and adherence to ISO standards for biocompatibility, not by expert consensus or interpretation of images.

4. Adjudication method for the test set
Not applicable. The tests are based on objective, quantifiable measurements against pre-defined specifications and ISO standards, not on subjective assessment requiring adjudication among experts.

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 a material science study of a dental bonding agent, not a diagnostic device involving human readers or AI assistance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a material science study, not an AI algorithm.

7. The type of ground truth used
The ground truth is based on:

• Company specifications (1AB-1500-3-10706): For properties like appearance, curing, application characteristics, color, pH, and refraction index.
• Quantitative measurements: For bond strength (measured in MPa).
• Microscopic observation: For sealing property of dentin tubules (using SEM).
• International Standards (ISO 10993 series): For biocompatibility, specifically ISO 10993-5 (cytotoxicity) and ISO 10993-10 (sensitivity, irritation).

8. The sample size for the training set
Not applicable. This document describes performance validation against a predicate device and established standards, not the training of a machine learning model.

9. How the ground truth for the training set was established
Not applicable, as no training set for an algorithm is mentioned or implied.

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1. Fabrication of temporary crowns, bridges, inlays, onlays and veneers
2. Fabrication of long-term temporary restorations

GC Temp PRINT is 3D printable light curing composite for temporary crown and bridge. The device consists of a paste delivered in a bottle. GC Temp PRINT is fabricated with certain Digital Light Processing/Stereolithography Apparatus (DLP/SLA)a` 3D printers and post cured with light curing device into dental restorations, which are then bonded to tooth structure with adhesive temporary cement.

The provided text is a 510(k) summary for a dental device called "GC Temp PRINT". This document primarily focuses on establishing substantial equivalence to predicate devices, rather than describing a study proving the device meets specific acceptance criteria in the context of AI/ML performance.

Therefore, the requested information regarding acceptance criteria and performance study for AI/ML aspects cannot be fully provided from the given document as it refers to material properties and biocompatibility, not AI/ML performance.

However, I can extract the acceptance criteria and the bench test results for the physical properties of the GC Temp PRINT device as described in Section 6, "Performance Bench Tests".

1. Table of Acceptance Criteria and Reported Device Performance

Regarding the AI/ML-specific questions (2-9), the provided document does not contain this information as it describes a physical material, not an AI/ML device.

Here's why each AI/ML question cannot be answered:

• 2. Sample size used for the test set and the data provenance: Not an AI/ML device.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable for material property testing.
• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable for material property testing.
• 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 an AI/ML device.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not an AI/ML device.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): The ground truth for material properties is defined by established international standards (ISO) and company specifications, measured objectively.
• 8. The sample size for the training set: Not an AI/ML device, so no training set.
• 9. How the ground truth for the training set was established: Not an AI/ML device, so no training set with ground truth.

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1. Pit & Fissure Sealant and Root Surface Sealant
2. Hypersensitivity due to abrasion and early non-cavitated lesions
3. Protection immature enamel
4. Temporary filling including endodontic access

GC Fuji Triage EP is a bioactive glass ionomer for temporary restorative material. The device consists of powder and liquid filled in a capsule and is mixed with a capsule mixer. Then, the mixture is applied directly to a cavity with a capsule applier. As an additional improvement, a proprietary elongation tip can be attached to the capsule nozzle which enables access to small or deep cavities. GC Fuji Triage EP contains CPP-ACP (casein phosphopeptide - amorphous calcium phosphate) in the formulation. CPP-ACP was added to moderate the strength of cement for its use and provide a source of Ca+ and HP04-2. CPP-ACP was chosen as the additive for regulating the strength because it does not interfere with the setting reaction of the material.

The provided document is a 510(k) summary for the GC Fuji Triage EP dental cement. It focuses on demonstrating substantial equivalence to a predicate device and does not contain information typically found in a clinical study report that would outline acceptance criteria, study design, and results for a medical device with an algorithmic component.

Therefore, I cannot provide the requested information regarding acceptance criteria and study details as they are not present in the provided text. The document describes a non-clinical performance testing for a dental cement, not a study involving human readers or AI algorithms.

Here's why each point of your request cannot be answered based on the provided text:

1. A table of acceptance criteria and the reported device performance: While there is a table of "Property" and "Requirements" for non-clinical performance (e.g., Net setting time, Compressive strength), this is for the physical properties of the dental cement, not the performance of an AI device. The document explicitly states "No clinical testing has been performed on this device."
2. Sample size used for the test set and the data provenance: Not applicable. There is no test set in the context of an AI device.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. There is no test set for an AI device, and thus no ground truth established by experts in that context.
4. Adjudication method (e.g. 2+1, 3+1, none) 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. No MRMC study was performed as this is a dental cement, not an AI-powered diagnostic device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an algorithm-based device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable to an AI device. The ground truth for the dental cement is based on laboratory-measured physical properties against ISO standards.
8. The sample size for the training set: Not applicable. There is no training set mentioned, as this is not a machine learning or AI device.
9. How the ground truth for the training set was established: Not applicable.

The document pertains to the regulatory submission for a dental cement, GC Fuji Triage EP, and focuses on demonstrating its safety and efficacy through biocompatibility testing (ISO 10993-1:2018, ISO 10993-5, ISO 10993-10) and physical property testing against ISO 9917-1:2007 for water-based cements, as well as comparison to a predicate device for substantial equivalence.

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everX Flow is a reinforcing dentin replacement material suitable for:

• 1. All direct composite restorations including large posterior cavities.
• 2. Deep cavities and endo-treated teeth.
• 3. Cavities with missing cusps or after amalgam removal and cavities where inlays would also be recommended.
• 4. Core build-up

everX Flow is a light cured, short-fiber-reinforced composite for dentin replacement for the restoration of posterior and anterior teeth. EverX Flow is filled in a syringe. The material is available in two shades, Bulk shade and Dentin shade.

The provided document pertains to a 510(k) premarket notification for a dental device named "everX Flow," a tooth shade resin material. This document focuses on demonstrating substantial equivalence to legally marketed predicate devices, primarily through bench testing (performance testing) and biocompatibility assessment, rather than clinical performance testing involving human subjects or AI-assisted diagnostic studies.

Therefore, many of the requested details regarding acceptance criteria, study methodologies (like sample size for test sets, number of experts, adjudication, MRMC studies, standalone AI performance), and ground truth establishment for a diagnostic AI device are not applicable to this submission. This is a material science and dental product regulatory submission, not a medical AI/software as a medical device (SaMD) submission.

However, I can extract and present the acceptance criteria and performance data that are relevant to this type of device, which is primarily laboratory bench testing.

Acceptance Criteria and Reported Device Performance for everX Flow (Dental Resin Material)

This device, "everX Flow," is a dental restorative material, not an AI or diagnostic device. Therefore, the "acceptance criteria" refer to the physical, chemical, and biological properties of the material itself, as tested in a laboratory setting according to international standards (ISO 4049:2009 and ISO 10993-1:2009 for biocompatibility).

1. Table of Acceptance Criteria and Reported Device Performance

Study Proving Device Meets Acceptance Criteria:

The study proving the device meets the acceptance criteria is a series of non-clinical performance bench tests and biocompatibility assessments.

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

• Sample Size for Test Set: The document does not specify exact sample sizes for each bench test (e.g., how many specimens were tested for flexural strength). It broadly states that "Performance testing includes" a list of properties and that the device "complies with all the requirements of ISO 4049: 2009." ISO standards typically define the minimum number of samples for each test, and the claim of compliance implies these were followed.
• Data Provenance: The tests were conducted internally by the manufacturer (GC Corporation) or a contracted lab. The data is prospective, generated specifically for this regulatory submission. The country of origin of the data is not explicitly stated but is implicitly Japan, as GC Corporation is the manufacturer.

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

• Not Applicable. This is a material properties test, not a diagnostic study requiring expert human interpretation. The "ground truth" is defined by established international standards (ISO 4049:2009) and the results are quantifiable physical/chemical measurements.

4. Adjudication Method for the Test Set

• Not Applicable. As this involves objective laboratory measurements against defined standards, there is no human interpretation or adjudication process required for the primary test results.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and its effect size

• Not Applicable. This is a dental material, not a diagnostic AI system or medical imaging device. No MRMC study was conducted. The relevant comparison in this submission is the "substantial equivalence" of the material's properties (composition, curing mechanism, performance characteristics) to existing predicate devices.

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

• Not Applicable. This product is a physical dental material; it does not contain or rely on an algorithm or AI.

7. The type of ground truth used

• Defined Standards and Objective Measurements: The "ground truth" for the performance tests is established by the specified requirements in ISO 4049:2009 for dental polymer-based restorative materials. The measurements (e.g., depth in mm, strength in MPa, mass change in µg/mm³) are objective and quantitative. For biocompatibility, the ground truth is established by the guidelines of ISO 10993-5 (in vitro cytotoxicity).

8. The sample size for the training set

• Not Applicable. This product is a physical dental material, not an AI model that requires a training set.

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

• Not Applicable. As there is no training set, there is no ground truth establishment for one. The development of the material itself would involve R&D and quality control processes, but not "ground truth establishment" in the AI/diagnostic sense.

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• -Cementation of metal-based inlays, onlays, crowns and bridges
• -Cementation of resin inlays, onlays, crowns and bridges
• Cementation of all ceramic inlays -
• -Cementation of high strength (e.g. zirconia based, lithium disilicate) ceramic onlays, crowns and bridges
• Cementation of metal, ceramic and fiber posts -

GC FujiCEM 2 (Improved) is a resin modified glass ionomer luting cement. The device is composed of the two pastes, Paste A and Paste B, packaged in an automix dual barrel syringe.

The provided document is a 510(k) summary for a dental cement (GC FujiCEM 2 (Improved)). It focuses on demonstrating substantial equivalence to a predicate device through non-clinical performance testing. It does not contain information about software or AI-based devices. Therefore, a table of acceptance criteria and reported device performance for an AI/software device cannot be generated from this text.

The document discusses the physical and chemical properties of the dental cement through performance bench tests and biocompatibility assessments against established ISO standards.

Here's an analysis of the available information regarding the device's evaluation, although it's for a physical dental cement product, not an AI device:

1. Table of Acceptance Criteria and Reported Device Performance (Non-AI/Software):

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

• Not applicable for AI/Software. The document describes non-clinical bench testing. The sample sizes for each specific test (e.g., number of specimens for flexural strength) are not explicitly stated within this summary. Data provenance is implied to be from the manufacturer's own testing.

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

• Not applicable for AI/Software. Ground truth for dental cement properties is established through standardized physical and chemical testing methods, not expert consensus in the way it's used for AI diagnostic outputs.

4. Adjudication method for the test set:

• Not applicable for AI/Software. The performance criteria for the dental cement are objective metrics measured by equipment and standardized procedures, not subjective interpretations requiring adjudication.

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 document is for a dental cement, not an AI or software device.

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

• Not applicable. This is a physical medical device (dental cement), not an algorithm or software. No standalone algorithm performance was assessed.

7. The type of ground truth used:

• For biocompatibility: Ground truth is defined by the criteria and methods outlined in ISO 10993 series standards.
• For performance bench tests: Ground truth is defined by the specifications and methods in ISO 9917-2: 2017 (Dentistry - Water-based cements - Part 2: Resin-modified cements) and the company's internal standards. These are objective, measurable physical and chemical properties.

8. The sample size for the training set:

• Not applicable. This is a physical medical device. There is no training set in the context of AI/machine learning.

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

• Not applicable. See point 8.

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Increases the adhesiveness of light-curing composites to conventional acrylic resins used in dental laboratory procedures (e.g., modification of denture teeth/denture base resins)

GC ACRYLIC PRIMER is a primer which raises the adhesiveness to acrylic resin and composite resin. GC ACRYLIC PRIMER is intended to use for bonding acrylics to acrylic resin, composite to composite resin, and acrylics to composite resin respectively.

The device in question is GC ACRYLIC PRIMER, a resin tooth bonding agent.

Here's a breakdown of the acceptance criteria and the study information provided:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify a distinct "test set" in the context of clinical or performance testing with human subjects or a defined dataset for AI. The performance bench tests appear to be conducted on the device itself.

• Sample Size for Test Set: Not explicitly stated for performance bench tests, but implied to be sufficient to demonstrate conformity to specifications.
• Data Provenance: Not applicable in the context of a "test set" as typically understood for AI/clinical studies. The performance data is generated from laboratory bench testing of the device.

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

Not applicable. The performance testing involves laboratory measurements and assessments against predefined physical and chemical specifications, not expert-derived ground truth on clinical data.

4. Adjudication method for the test set

Not applicable. The performance testing involves objective measurements rather than expert adjudication.

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 MRMC comparative effectiveness study was conducted. This device is a dental material (primer) and not an AI-powered diagnostic tool.

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

Not applicable. This device is a dental material, not an algorithm.

7. The type of ground truth used

The "ground truth" for the performance criteria is based on:

• Predefined physical and chemical specifications: For appearance, application characteristics, refractive index, and bond strength. These are objective laboratory measurements.
• Biocompatibility standards: ISO 10993-5 guidelines for cytotoxicity.

8. The sample size for the training set

Not applicable. This device is a dental material, not an AI model, and therefore does not have a training set.

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

Not applicable. This device is a dental material, not an AI model, and therefore does not have a training set or associated ground truth establishment.

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AIM2 is a silicone impression material for taking oral impressions.

AIM2 is a VPS silicone impression material. The components consist of the base silicone paste and the catalyst silicone paste that are extruded from a cartridge and are automixed with a mixing tip. AIM2 is available in one viscosity. The cartridge is made of high density polyethylene and the cap is made of polypropylene. The mixing tip is made of polypropylene.

This document describes the premarket notification (510(k)) for the dental impression material AIM2. It focuses on demonstrating that AIM2 is substantially equivalent to a predicate device, EXAFLEX/EXAMIX Impression Material (K955932).

Here's an analysis of the provided text in relation to acceptance criteria and supporting studies:

1. Table of Acceptance Criteria and Reported Device Performance:

The primary acceptance criteria mentioned are the specifications outlined in ISO 4823. The document states that the device conforms to these required specifications.

Note: The document explicitly states: "Results of benchtop testing indicate the physical properties such as linear dimensional change, elastic recover and strain-in compression met the specification set in ISO 4823." This is the direct evidence of meeting the acceptance criteria.

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

• Sample Size for Test Set: The document does not specify the sample size used for the benchtop tests.
• Data Provenance: The tests were "benchtop testing," which implies laboratory testing. The country of origin of the data is not specified, but the manufacturer is GC Corporation. The study is not a clinical trial, so the terms "retrospective" or "prospective" are not applicable in this context.

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

This information is not applicable as the study is a benchtop performance test against international standards (ISO 4823), not a study requiring expert interpretation of clinical data or images to establish ground truth.

4. Adjudication Method for the Test Set:

This information is not applicable for a benchtop performance test.

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:

This information is not applicable. The device is an impression material, not an AI-powered diagnostic or assistive tool for human readers.

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

This information is not applicable. The device is a physical impression material, not an algorithm.

7. The Type of Ground Truth Used:

For the performance tests, the "ground truth" or reference standard was the specifications outlined in ISO 4823. For biocompatibility, the document refers to the biological safety test data of the predicate device.

8. The Sample Size for the Training Set:

This information is not applicable as the device is a physical material and not an AI/ML algorithm that requires a training set.

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

This information is not applicable as the device does not involve a training set.

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1. Class III and V restorations
2. Restoration of primary teeth
3. Core build-up
4. Cases where radiopacity is required
5. Base material for Class I and Class II cavities using a sandwich laminate technique.

GC Fuji Direct is a light-cured resin-modified restorative glass ionomer cement. The device consists of two pastes filled in a Paste Pak Cartridge. Paste A and B are dispensed with Paste Pak Dispenser II and hand mixed. Paste A and B can also be automixed by attaching the GC Fuji Direct Mixing Tip to the Paste Pak Dispenser II and applied directly to the prepared cavity. The bioactive material sets by acid-base reaction of fluoroalumino-silicate glass and Polyacrylic acid, and polymerization of methacrylate monomers.

Here's a breakdown of the acceptance criteria and study information based on the provided text, structured to include all your requested points:

Acceptance Criteria and Device Performance

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document primarily describes bench testing against ISO standards and biocompatibility assessments. Therefore, there isn't a "test set" in the context of a clinical study with human or biological samples in the way this question typically implies for AI/diagnostic devices. The data provenance is related to laboratory testing, likely conducted by or for GC America Inc., a US-based company, referencing the specified international standards. No country of origin for the specific test data is given beyond the company's location. The testing appears to be prospective (as part of the 510(k) submission).

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

N/A. This is a bench test and biocompatibility assessment against technical specifications rather than an evaluation requiring expert-established ground truth on a test set (e.g., medical image interpretation). The "ground truth" for these tests is the quantitative and qualitative requirements of the ISO standard.

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

N/A. This is a bench test against technical specifications, not a study requiring adjudication of expert interpretations.

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

N/A. This device is a dental cement, not an AI software/diagnostic device that would typically involve human readers or AI assistance.

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

N/A. This device is a dental cement, not an algorithm, so this question is not applicable.

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

The "ground truth" for the performance testing is adherence to the technical specifications defined in ISO 9917-2:2010 (Dentistry - Water-based cements - Part 2: Resin-modified cements) and the protocols outlined in ISO 10993-1:2009, ISO 10993-5, and ISO 10993-10 for biocompatibility. These are objective, predefined standards for material properties and biological response.

8. The sample size for the training set

N/A. This is a dental material, not an AI model, so there is no "training set."

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

N/A. As there is no training set for an AI model, this question is not applicable.

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