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The Surgical Face Masks are intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids and particulate material. These mask 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 ear loops and nose piece. The Surgical Face 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 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 polypropylene with steel wire. The colorants used for mask are Copper phthalocyanine, Titanium dioxide and Polyethylene. The proposed devices are sold non-sterile and are intended to be single use, disposable devices. The proposed device including two models, WXDKZ0001 and WXDKZ0006, the difference is the color of the outer layer.

The provided text is a 510(k) summary for a Surgical Face Mask and focuses on demonstrating substantial equivalence to a predicate device based on non-clinical bench testing and biocompatibility assessments, not on studies involving AI/ML models or human readers.

Therefore, I cannot extract the information required by your prompt regarding acceptance criteria and studies proving an AI/ML device's performance, as the document describes a traditional medical device (face mask).

The prompt's questions pertain to:

1. AI/ML model acceptance criteria and performance.
2. Sample sizes for test and training sets (implying data used for model development/validation).
3. Expert ground truth establishment and adjudication (relevant for medical imaging AI).
4. MRMC studies (relevant for AI-assisted human performance).
5. Standalone AI performance.
6. Type of ground truth (pathology, outcomes data, etc.).

None of these concepts are discussed in the provided text, which details the physical and material characteristics, intended use, and performance standards (e.g., fluid resistance, filtration efficiency, flammability, biocompatibility) of a surgical face mask.

The document explicitly states:

• "No clinical tests were performed" (Section 9).
• The tests mentioned are "Bench testing" and "Biocompatibility testing" of the physical mask.

To accurately answer your request, you would need a document describing the regulatory submission for an AI/ML-driven medical device.

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