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MIRACLE 98 is intended for manufacturing: - Porcelain to metal fabrication of single units

MIRACLE 98 is a High Noble, Micro-fine, Yellow, Gold based alloy to be used for single unit with lower fusing porcelains and indirect restorative composites. MIRACLE 98 is a high gold ceramic alloy, which heightens the porcelain esthetics of the restoration and provides strength, durability and color of gold.

The request is to describe the acceptance criteria and the study that proves the device meets the acceptance criteria based on the provided text.

Based on the provided 510(k) summary for the "MIRACLE 98" dental casting alloy, the device is a Class II device (Gold-based alloys and precious metal alloys for clinical use). The approval is based on substantial equivalence to a predicate device, Heraeous Kulzer's Jel Bios Pure (K002645), rather than a clinical study with acceptance criteria in the typical sense of a diagnostic or AI device.

Here's the information formatted as requested, with "N/A" where the information is not applicable to this type of device and submission:

Acceptance Criteria and Device Performance for MIRACLE 98 (K031010)

This submission relies on demonstrating substantial equivalence to a legally marketed predicate device (Heraeous Kulzer's Jel Bios Pure, K002645) by comparing material composition and physical/mechanical properties. The "acceptance criteria" are implied by the similarity of these characteristics to the predicate.

1. Table of Acceptance Criteria and Reported Device Performance

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AIGIS-PLUS is intended for manufacturing

• Inlay / Onlays …
• Crowns -
• Short span bridges -
• Long span bridges -
• Removable partials -

AIGIS-PLUS is an inlay, onlay, crown and bridge alloy. This device is dependable 56% gold alloy with a high gold appearance. AIGIS-PLUS is excellent for inlays, three-quarter crowns, long and short-span bridges.

This 510(k) summary describes a dental casting alloy, AIGIS-PLUS, and aims to demonstrate its substantial equivalence to a legally marketed predicate device, ARGENCO 56. The study focuses on comparing the physical and mechanical properties and composition of the two alloys.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are not explicitly stated as numerical targets in the document. Instead, the "acceptance criteria" are implied by the comparison to the predicate device, ARGENCO 56. The device is considered to meet acceptance criteria if its properties are "very similar" or "almost identical" to the predicate, with "minor differences" that "do not affect safety or effectiveness."

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

This document does not specify a separate "test set" in the context of typical algorithm validation. The "study" here is a comparison of material properties.

• Sample Size: Not explicitly stated. The table presents single values for each property, implying these are average or representative values obtained from testing unspecified sample sizes of both ARGENCO 56 and AIGIS-PLUS.
• Data Provenance: Not explicitly stated. It is implied that the data for AIGIS-PLUS was generated by the submitter (SB Lucius, Inc.) through their own testing, as they are providing this information for their new device. The data for ARGENCO 56 would presumably be from its existing regulatory submission or published material data. The country of origin for the data is not mentioned, but the submitter is based in Anaheim, CA, USA. The study is retrospective in the sense that the predicate device's data is pre-existing; the testing of AIGIS-PLUS to generate its performance data would be prospective.

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

Not applicable. This is not a study involving expert review for establishing ground truth, but rather a materials science comparison. The "ground truth" here is the measured physical and mechanical properties of the alloys.

4. Adjudication Method for the Test Set

Not applicable. There is no adjudication method described as it's not and expert-based review. The comparison is based on objective measurements against a predicate device.

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 a diagnostic device or an AI-enabled device. It is a dental casting alloy.

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

Not applicable. This is not an algorithm or AI-enabled device.

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

The "ground truth" for this study is based on standardized materials testing of the physical and mechanical properties of the dental alloys, as described by "Test methods applied: as in ANSI/ADA 5 and ISO 9693." These standards define the procedures for measuring properties like melting point, hardness, yield strength, elongation, and density.

8. The sample size for the training set

Not applicable. There is no training set for this type of material comparison study.

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

Not applicable, as there is no training set.

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AIGIS-SOFT is intended for manufacturing

• Inlay / Onlays -
• Crowns -
• Short span bridges -
• Long span bridges "
• Removable partials -

AIGIS-SOFT is an inlay, onlay, crown and bridge alloy. This device is dependable 83% gold alloy with a high gold appearance. AIGIS-SOFT is excellent for inlays, three-quarter crowns, long and short-span bridges.

Here's an analysis of the provided text regarding the AIGIS-SOFT device, focusing on acceptance criteria and the supporting study:

Key Takeaway: This 510(k) summary is for a dental casting alloy, not a software or AI-driven medical device. Therefore, the questions regarding AI performance, reader studies, ground truth establishment for algorithms, and training set sizes are not applicable to this submission. The "study" described is a comparison of material properties to a predicate device.

Acceptance Criteria and Device Performance

The acceptance criteria for AIGIS-SOFT are not explicitly stated as numerical targets in the same way one might find for a diagnostic device. Instead, the "acceptance criteria" are implicitly met by demonstrating substantial equivalence to a legally marketed predicate device (ARGENCO 83) based on composition and physical/mechanical properties. The performance is assessed by comparing these properties.

Table of Acceptance Criteria and Reported Device Performance

Summary of the Study:

The study proving the device meets the acceptance criteria is a comparison study against a predicate device, ARGENCO 83 (K893384). The core of the study involved:

1. Chemical Composition Analysis: Comparing the elemental composition (though specific percentages are not fully tabulated for both in the provided text). The submission states, "The main elements and their concentration are almost identical."
2. Physical and Mechanical Properties Testing: Measuring key properties such as melting point, hardness, yield strength, elongation, and density for both AIGIS-SOFT and the predicate device. These are presented in a direct comparison table.

The conclusion drawn from this comparative study is that "AIGIS-SOFT is substantially equivalent to ARGENCO 83 and the minor differences between them do not affect safety or effectiveness."

Specific Information Requested:

Given the nature of the device (a dental alloy), most of the requested points related to AI/software performance are not applicable.

1. Table of Acceptance Criteria and Reported Device Performance: (See table above). The acceptance criterion is "substantial equivalence" to the predicate, with reported performance being the direct comparison of material properties.

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

   • Sample Size: Not specified in terms of number of units of alloy tested, but implies standard material testing methods (e.g., tensile tests, hardness measurements) would involve multiple samples. No "test set" in the context of an algorithm.
   • Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). It's standard materials testing data, likely generated in a lab setting.

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

   • N/A. This is a material properties comparison; there's no "ground truth" established by human experts in the context of diagnostic interpretation. Physical measurements (e.g., melting point, hardness) are empirically determined.

4. Adjudication Method (e.g., 2+1, 3+1, none) for the Test Set:

   • N/A. No expert adjudication is applicable for material property measurements.

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. AIGIS-SOFT is a physical dental alloy, not an AI or imaging device, so no MRMC study was performed.

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

   • N/A. This is not an algorithm.

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

   • Empirical Measurement Data: The "ground truth" for the properties comes from direct physical and chemical measurements (e.g., melting point via calorimetry, hardness via Vickers indenter, elemental composition via spectroscopic methods). The "truth" for biocompatibility is inferred from chemical similarity.

8. The sample size for the training set:

   • N/A. There is no "training set" as this is not a machine learning algorithm.

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

   • N/A. Not applicable, as there is no training set for an algorithm.

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AIGIS-SUPER is intended for manufacturing

• Inlay / Onlays -
• Crowns -
• Short span bridges -
• Long span bridges -
• Removable partials -

AIGIS-SUPER is an inlay, onlay, crown and bridge alloy. This device is dependable 53% gold alloy with a high gold appearance. AIGIS-SUPER is excellent for inlays, three-quarter crowns, long and short-span bridges.

The provided document is a 510(k) summary for a dental casting alloy named AIGIS-SUPER. The purpose of this submission is to demonstrate substantial equivalence to a predicate device, JENSEN'S JYE. The focus of the evaluation is on the material properties, not an AI/ML device.

Therefore, many of the questions regarding acceptance criteria for an AI/ML device, such as sample size for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, and training set details, are not applicable to this document.

However, I can extract the acceptance criteria and performance data related to the physical and mechanical properties of the dental alloy.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for AIGIS-SUPER are implicitly defined by its substantial equivalence to the predicate device, JENSEN'S JYE. While explicit numerical ranges for acceptance aren't provided, the comparison of properties indicates that AIGIS-SUPER should have similar or acceptable ranges for these properties.

Study Proving Acceptance Criteria:

The study that proves the device meets the acceptance criteria is a comparison of technological characteristics, specifically focusing on the composition and physical/mechanical properties. The test methods applied are stated as per ANSI/ADA 5 and ISO 9693.

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

• Sample Size: Not explicitly stated for each test (e.g., how many samples were tested for hardness, melting point). The document presents summary values.
• Data Provenance: Not specified. It's a manufacturing specification/test rather than clinical data.

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

• Not applicable as this is not a diagnostic device involving expert interpretation of medical images or data. The "ground truth" here is the measured physical and mechanical properties of the material, assessed against established standards (ANSI/ADA 5 and ISO 9693) and comparison to the predicate device.

4. Adjudication method for the test set:

• Not applicable. This is not a study requiring adjudication of expert opinions.

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/ML device, and no MRMC study was conducted.

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

• Not applicable. This is not an AI/ML device.

7. The type of ground truth used:

• The "ground truth" in this context is the measured physical and mechanical properties of the dental alloy, determined through standardized test methods (ANSI/ADA 5 and ISO 9693). This is compared against the known properties of the legally marketed predicate device (JENSEN'S JYE).

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 AI sense.

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

• Not applicable. No training set for an AI/ML model.

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AIGIS-FINE is intended for manufacturing

• Inlay / Onlays -
• Crowns -
• Short span bridges -
• Long span bridges -
• Removable partials -

AIGIS-FINE is an inlay, onlay, crown and bridge alloy. This device is dependable 7 1% gold alloy with a high gold appearance. AIGIS-FINE is excellent for inlays, three-quarter crowns, long and short-span bridges.

This 510(k) summary describes a dental casting alloy, AIGIS-FINE, and its substantial equivalence to a predicate device, AUROFLUID M. The substantial equivalence is based on a comparison of composition and physical/mechanical properties.

Here's a breakdown of the requested information:

1. Table of acceptance criteria and the reported device performance

The acceptance criteria are implicitly defined by the properties of the predicate device, AUROFLUID M. The newer device, AIGIS-FINE, is considered acceptable if its properties are substantially equivalent and do not negatively impact safety or effectiveness.

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

• Sample Size: Not explicitly stated. The comparison is made based on material properties, which are typically derived from standardized testing of material samples. The text does not provide details on the number of samples tested for each property.
• Data Provenance: Not explicitly stated. The data is presented as a comparison between the applicant's device (AIGIS-FINE) and a legally marketed predicate (AUROFLUID M). It's reasonable to assume the AIGIS-FINE data was generated by the applicant (SB LUCIUS, INC.), likely from laboratory testing. The provenance of the AUROFLUID M data is not mentioned but would have been established during its own regulatory approval. The study is retrospective in the sense that it relies on existing data for the predicate device and newly generated data for the proposed device for comparison.

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

This type of study does not involve experts establishing ground truth for a test set in the way a diagnostic imaging AI algorithm would. Instead, the "ground truth" for material properties is established through standardized laboratory testing (as in ANSI/ADA 5 and ISO 9693). The results of these tests (melting point, hardness, yield strength, etc.) are objective measurements, not subjective expert opinions.

4. Adjudication method for the test set

Not applicable. There is no adjudication method described as this is a comparison of material properties, not a review 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

Not applicable. This is a comparison of material properties for a dental casting alloy, not a diagnostic imaging device involving human readers or AI.

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

Not applicable. This is a material science comparison, not an algorithmic performance study.

7. The type of ground truth used

The ground truth used is based on standardized physical and mechanical property measurements of the dental alloy. These are objective laboratory measurements, not expert consensus, pathology, or outcomes data.

8. The sample size for the training set

Not applicable. This is not a machine learning study, so there is no concept of 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 established for it.

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AIGIS-INLAY is intended for manufacturing

• Inlay / Onlays -
• Crowns -
• Short span bridges -
• Long span bridges -
• Removable partials

Dental casting alloy

This 510(k) summary describes a dental casting alloy, AIGIS-INLAY, and asserts its substantial equivalence to a legally marketed predicate device, DEGULOR A. The acceptance criteria and the study proving it meets these criteria are based on direct comparison of physical and mechanical properties and composition.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are established by comparing the AIGIS-INLAY to the predicate device, DEGULOR A, based on specific physical and mechanical properties, and composition. The underlying standard referenced is ANSI/ADA 5 and ISO 9693. Given this is a material comparison for substantial equivalence, the "acceptance criteria" are effectively that the new device's properties are "very similar" or fall within an acceptable range compared to the predicate.

Study to Prove Acceptance Criteria:

The study used to prove the device meets the acceptance criteria is a direct comparison of composition and physical/mechanical properties between the AIGIS-INLAY and the predicate device, DEGULOR A. The methods applied are "as in ANSI/ADA 5 and ISO 9693," which are international standards for dental casting alloys. The conclusion reached is that the AIGIS-INLAY is "substantially equivalent" to DEGULOR A, and "minor differences between them do not affect safety or effectiveness."

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

• Sample Size: Not specified. The document presents single-point values for each property for both the predicate and the new device. It does not provide information on the number of samples tested to arrive at these values.
• Data Provenance: Not specified. It can be assumed that the data for AIGIS-INLAY was generated by the manufacturer (SB LUCIUS, INC.)
• Retrospective or Prospective: Not applicable as this is a material properties comparison, not a clinical study.

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

Not applicable. The ground truth for this device (a dental casting alloy) is established by comparing its physical and mechanical properties against recognized dental material standards (ANSI/ADA 5 and ISO 9693) and a legally marketed predicate device, not by expert consensus on clinical cases.

4. Adjudication method for the test set:

Not applicable. This is a technical comparison of material properties, not a study requiring adjudication of clinical findings or 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:

Not applicable. This document pertains to a dental casting alloy, 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 document pertains to a dental casting alloy, not an algorithm.

7. The type of ground truth used:

The ground truth used is primarily physical and mechanical property measurements as defined by the standards ANSI/ADA 5 and ISO 9693, and chemical composition analysis. The properties of the predicate device (DEGULOR A) serve as the benchmark for substantial equivalence.

8. The sample size for the training set:

Not applicable. This is a device substantial equivalence submission, not a machine learning model.

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

Not applicable. This is a device substantial equivalence submission, not a machine learning model.

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AIGIS-PT is intended for manufacturing

• Inlay / Onlays -
• Crowns -
• Short span bridges -
• Long span bridges -
• Removable partials -

AIGIS-PT is an inlay, onlay, crown and bridge alloy. This device is dependable 77% gold alloy with a high gold appearance. AIGIS-PT is excellent for inlays, three-quarter crowns, long and short-span bridges.

Here's a summary of the acceptance criteria and the study for the AIGIS-PT device, based on the provided text.

Based on the provided 510(k) summary, AIGIS-PT is a dental casting alloy, and its acceptance criteria and study are based on demonstrating substantial equivalence to a legally marketed predicate device (AUROFLUID 2PF) through comparisons of chemical composition and physical/mechanical properties, according to established standards. This is not a study of an AI-based medical device, but rather a traditional materials science regulatory submission. Therefore, many of the requested fields related to AI device performance (like sample sizes for test sets, expert ground truth, MRMC studies, standalone performance) are not applicable.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implied by the comparison to the predicate device and the adherence to industry standards. The reported device performance is presented in comparison to the predicate.

Conclusion from data: The submission concludes that "AIGIS-PT is substantially equivalent to AUROFLUID 2PF and the minor differences between them do not affect safety or effectiveness."

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

• Sample Size for Test Set: Not applicable. This is a material characterization rather than a clinical study involving a "test set" in the context of AI. The properties are inherent to the material formulation.
• Data Provenance: Not specified, but likely from laboratory testing conducted by the manufacturer, SB Lucius, Inc.

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

• Number of Experts: Not applicable. Ground truth for material properties is established through standardized laboratory testing, not expert consensus.
• Qualifications of Experts: N/A

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. Material properties are measured objectively.

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

• MRMC Study: No. This is not a study assessing reader performance with or without AI.

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

• Standalone Study: No. This is not an AI device.

7. The Type of Ground Truth Used

• Type of Ground Truth: The "ground truth" for the device's properties is established through standardized laboratory testing as per ANSI/ADA 5 and ISO 9693 standards. These standards define the methods for measuring properties like melting point, hardness, yield strength, elongation, and density.

8. The Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. This is not an AI device that requires a "training set."

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

• How Ground Truth was Established: Not applicable.

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AIGIS-XO is intended for manufacturing

• Inlay / Onlays -
• Crowns -
• Short span bridges "
• Long span bridges -
• Removable partials -

AIGIS-XO is an inlay, onlay, crown and bridge alloy. This device is dependable 82% gold alloy with a high gold appearance. AIGIS-XO is excellent for inlays, three-quarter crowns, long and short-span bridges.

The provided text does not contain information about acceptance criteria or a study that proves a device meets such criteria in the context of a medical AI device.

Instead, the document is a 510(k) summary for a dental casting alloy named "AIGIS-XO," seeking market clearance as a Class II medical device. The 510(k) process is for demonstrating substantial equivalence to a legally marketed predicate device, not for proving performance against specific acceptance criteria for AI algorithms.

Here's why the requested information cannot be extracted from this document:

• Device Type: The device is "AIGIS-XO, Dental casting alloy" (a physical material), not an AI-powered diagnostic or assistive tool.
• Study Type: The document describes a comparison of the new device (AIGIS-XO) to a predicate device (BIOCLUS 4) based on composition and physical/mechanical properties (e.g., melting point, hardness, yield strength, elongation, density), not performance metrics like sensitivity, specificity, or reader agreement that would be relevant for an AI study.
• No AI Component: There is no mention of any AI algorithm, machine learning, deep learning, or digital imaging analysis.
• No Human Reader Studies: Since it's a dental alloy, there are no human reader studies (MRMC or standalone) involved.
• No Training/Test Sets: The concepts of training sets, test sets, ground truth established by experts, or adjudication methods are not applicable to the documentation of a dental alloy's properties.

Therefore, I cannot provide the requested table and study details as they pertain to AI device evaluation. The document focuses on demonstrating chemical and physical property similarities to an existing device to establish substantial equivalence.

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AIGIS-A is intended for manufacturing

• Inlay / Onlays -
• Crowns -
• Short span bridges -
• Long span bridges -
• Removable partials -

AIGIS-A is an inlay, onlay, crown and bridge alloy. This device is dependable 48% gold alloy with a high gold appearance. AIGIS-A is excellent for inlays, threequarter crowns, long and short-span bridges.

The provided document describes a 510(k) premarket notification for a dental casting alloy named AIGIS-A. The submission focuses on demonstrating substantial equivalence to a predicate device (JENSEN'S JMC) rather than presenting a study with specific acceptance criteria related to AI or algorithmic performance. Therefore, many of the requested categories (e.g., sample size for test set, number of experts, MRMC study, training set details) are not applicable to this type of submission.

Here's a breakdown based on the information available:

Acceptance Criteria and Device Performance (AIGIS-A vs. JENSEN'S JMC)

The acceptance criteria for this device are implicitly tied to demonstrating substantial equivalence to the predicate device, JENSEN'S JMC, by showing comparable composition and physical/mechanical properties, and suitability for the same indications for use.

Study Information:

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

   • N/A. This submission is for a material (dental casting alloy), not an AI/algorithm-driven device. Performance is demonstrated through material characterization tests (as per ANSI/ADA 5 and ISO 9693), not a clinical 'test set' in the context of AI. The data provenance would be from laboratory testing; specific details are not provided beyond the standards referenced.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

   • N/A. Ground truth for material properties is established through standardized laboratory testing, not expert consensus on interpretations.

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

   • N/A. Adjudication methods are not relevant for material property testing.

4. 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 is not an AI-powered device.

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

   • N/A. This is not an AI-powered device.

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

   • The "ground truth" for this device constitutes the established quantitative measurements of its physical and mechanical properties, obtained through standardized test methods (ANSI/ADA 5 and ISO 9693).

7. The sample size for the training set:

   • N/A. This is not an AI-powered device.

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

   • N/A. This is not an AI-powered device.

Summary of Acceptance:

The device, AIGIS-A, met the acceptance criteria by demonstrating substantial equivalence in composition, physical properties (melting point, hardness, elongation, density), and intended use to the legally marketed predicate device, JENSEN'S JMC. The minor differences in properties, such as a slightly lower yield strength, were deemed not to affect safety or effectiveness, as stated in the conclusion: "AIGIS-A is substantially equivalent to JENSEN'S JMC and the minor differences between them do not affect safety or effectiveness."

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NEO 76 is intended for manufacturing

• Inlay / Onlays -
• Crowns -
• Short span bridges -
• Long span bridges -
• Removable partials -

NEO 76 is an inlay, onlay, crown and bridge alloy. This device is dependable 76% gold alloy with a high gold appearance. NEO 76 is excellent for inlays, threequarter crowns, long and short-span bridges.

The provided text describes the 510(k) summary for the dental casting alloy, NEO 76. This submission aims to prove substantial equivalence to a predicate device, ARGENCO 77, rather than establishing acceptance criteria and conducting a study to meet them in the traditional sense of a performance study measuring clinical outcomes.

Instead, the "acceptance criteria" here relate to the demonstration of similar technological characteristics to the predicate device, thereby inferring similar safety and effectiveness. The "study" refers to the comparison of composition, physical, and mechanical properties between the new device (NEO 76) and the predicate device (ARGENCO 77).

Here's an analysis based on the provided information:

1. A table of acceptance criteria and the reported device performance

Since this is a substantial equivalence submission for a material, the "acceptance criteria" are implied to be the ranges and values of the predicate device's properties. The new device's performance is then compared to these.

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

The document does not specify sample sizes for testing or data provenance. The data presented are likely from laboratory tests conducted on the materials. It's a technical comparison of material properties, not a clinical study involving patients.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This section is not applicable. The "ground truth" for material properties is established by standardized testing methods (ANSI/ADA 5 and ISO 9693), not by expert consensus on clinical cases.

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

This section is not applicable. Adjudication methods are typically for clinical case review, not 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

There was no MRMC comparative effectiveness study. This device is a dental casting alloy, not an imaging device or AI-assisted diagnostic tool.

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

This section is not applicable. This is a material, not an algorithm.

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

The "ground truth" for the comparison is established by standardized material testing methods (ANSI/ADA 5 and ISO 9693) for physical and mechanical properties. For composition, elemental analysis would be used.

8. The sample size for the training set

This section is not applicable. There is no "training set" in the context of material property comparison for substantial equivalence.

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

This section is not applicable. There is no "training set" or corresponding ground truth establishment in this type of submission.

Summary of the Study (Comparison for Substantial Equivalence):

The study conducted was a technical comparison of compositional and physical/mechanical properties between the new device (NEO 76) and a legally marketed predicate device (ARGENCO 77).

• Methods: The comparison was based on test methods applied as in ANSI/ADA 5 and ISO 9693. These standards define the procedures for measuring specific material properties like melting point, hardness, yield strength, elongation, and density. Compositional analysis would also have been performed.
• Findings: The submitter concluded that "The main elements and their concentration are almost identical" and presented a table comparing key physical and mechanical properties. While there are some numerical differences (e.g., NEO 76 has a slightly higher melting point range, hardness, yield strength, elongation, and density), the submitter's argument for substantial equivalence is based on these differences not affecting safety or effectiveness.
• Conclusion for Substantial Equivalence: The FDA's letter (K024141) confirms that the device was found substantially equivalent to the predicate device, indicating that the submitted comparison adequately demonstrated that the minor differences do not raise new questions of safety or effectiveness.

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