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The Surgical Masks are intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids and particulate material. These masks are intended for use in infection control practices to reduce the potential exposure to blood and body fluids. This is a single use ,disposable device, provided non-sterile.

The proposed devices are single use, three-layer, flat masks with straps and nose piece. The Surgical Masks are manufactured with three layers, the inner and outer layers are made of spun-bond polypropylene, and the middle layer is made of melt blown polypropylene filter. The proposed device is held in place over the user's mouth and nose by two elastic ear loops or four ties welded to the face mask. The elastic ear loops are not made with natural rubber latex. The nose piece contained in the proposed device is in the layers of face mask to allow the user to fit the face mask around their nose, which is made of Malleable aluminum wire. The proposed devices are sold non-sterile and are intended to be single use, disposable devices.

The document provided is a 510(k) summary for a Disposable Surgical Mask, outlining its substantial equivalence to a legally marketed predicate device. As such, the information contained focuses on the device's physical properties, material composition, and performance against established safety and efficacy standards for surgical masks.

This type of submission and the associated testing do not involve AI/ML components, human reader studies, or complex ground truth establishment methods typical for AI/ML-driven medical devices. The tests described are laboratory-based evaluations of the mask's material properties and fluid/particulate blocking capabilities.

Therefore, many of the specific questions posed in your request (e.g., sample size for test set, number of experts for ground truth, adjudication method, MRMC studies, standalone performance, training set details) are not applicable to this disposable surgical mask submission.

Here's the relevant information based on the provided text:

Acceptance Criteria and Device Performance

The acceptance criteria are established based on recognized industrial standards for performance of materials used in medical face masks.

Table of Acceptance Criteria and Reported Device Performance

Study Details

1. Sample size used for the test set and the data provenance:
   The document does not specify the exact sample sizes (number of masks or material samples) used for each test. The tests are laboratory-based, performed on material samples of the mask. Data provenance is implied to be from the manufacturer's internal testing. There is no indication of patient data or clinical data; the study is entirely non-clinical. The origin of the testing would be where the manufacturer is located, which is Dongguan, China. The studies are retrospective laboratory tests on manufactured samples.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
   Not applicable. Ground truth for these performance tests is established by adhering to widely accepted international standards (e.g., ASTM, EN, ISO) and their specified testing methodologies and acceptance criteria. There are no "experts" in the human perception or diagnostic sense involved in establishing ground truth for these physical properties.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
   Not applicable. This concept pertains to expert review of data (e.g., medical images). The "ground truth" for these tests is the quantitative measurement of physical properties against a standard.

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:
   Not applicable. This is a simple medical device (disposable surgical mask), not an AI-assisted diagnostic tool. No human reader studies were performed.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
   Not applicable. There is no algorithm or AI component in this device. The "standalone performance" refers to the mask's inherent physical characteristics as tested in the laboratory.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
   The ground truth is defined by the acceptance criteria established by standardized, validated test methods (e.g., ASTM F1862 for fluid resistance, ASTM F2299 for particulate filtration efficiency), which are internationally recognized and specified in the FDA's guidance document for surgical masks. These are objective, measurable physical properties, not subjective interpretations or clinical outcomes.

7. The sample size for the training set:
   Not applicable. This device does not involve machine learning; therefore, there is no "training set."

8. How the ground truth for the training set was established:
   Not applicable, as there is no training set.

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