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Powdered Vinyl Patient Examination Gloves, Light Yellow Color is a non-sterile disposable device intended for medical purposes that is worn on the examiner's hand or finger to prevent contamination between patient and examiner.

Powdered Vinyl Patient Examination Gloves, Light Yellow Color that meets all of the requirements of ASTM standard D 5250-06e1.

The provided text describes a 510(k) summary for "Powdered Vinyl Patient Examination Gloves, Light Yellow Color." This is a medical device that falls under the category of general hospital devices, specifically patient examination gloves.

The text does not describe an AI/ML powered device, nor does it involve any studies related to human readers, AI assistance, or complex diagnostic tasks. The "acceptance criteria" and "study" described in the document are for basic physical, chemical, and biological properties of the gloves, not for an AI algorithm.

Therefore, I cannot extract the information required for the requested table and parameters related to an AI/ML device. The document pertains to a much simpler Class I medical device.

Here's a breakdown of why this document doesn't fit the request and what information can be extracted:

• No AI/ML Component: The device is a physical product (gloves), not a software or AI-driven system.
• No "Ground Truth" for AI: Concepts like expert consensus, pathology, or outcomes data as "ground truth" are irrelevant for examination gloves.
• No "Readers" or "Adjudication": There are no human readers or AI algorithms being evaluated in a diagnostic context.
• No "Sample Size for Test/Training Set" in AI Sense: The phrase "sample size" in this document refers to the quantity of gloves tested for physical properties (e.g., freedom from pinholes), not data points for an AI model.
• No "Effect Size of Human Readers Improve with AI": This is completely unrelated to the device described.

What can be extracted related to "acceptance criteria" from the provided text for this specific device:

The "acceptance criteria" are essentially the relevant ASTM standards and FDA regulations that the gloves must meet. The "device performance" is stated as "Meets" for all these criteria.

Table of Acceptance Criteria and Reported Device Performance (as per the document):

Regarding the other requested information (which is not applicable to this device type):

• Sample sized used for the test set and the data provenance: The document indicates that the product "meets" various ASTM standards and CFR regulations. These standards define the sampling plans for testing. For example, ASTM D5250 specifies various testing methods and sampling requirements (e.g., for physical properties, freedom from holes). However, the specific sample sizes used in this particular submission's tests are not detailed in the summary, only that the product met the standards. The data provenance is implied to be from the manufacturer's internal testing as part of their quality control and submission process, likely conducted in China (based on the manufacturer's location).
• Number of experts used to establish the ground truth...: Not applicable. Ground truth for a glove is its physical properties, not expert interpretation.
• Adjudication method for the test set: Not applicable.
• If a multi reader multi case (MRMC) comparative effectiveness study was done...: Not applicable.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• The type of ground truth used: For gloves, the "ground truth" is defined by the objective measurements and tests prescribed by the relevant ASTM standards and FDA regulations (e.g., tensile strength, elongation, barrier integrity, protein content, powder amount).
• The sample size for the training set: Not applicable as there is no "training set" for an AI model.
• How the ground truth for the training set was established: Not applicable.

In conclusion, the provided text describes a traditional medical device (patient examination gloves) and its regulatory compliance, not an AI/ML powered device. Therefore, the specific questions related to AI/ML device evaluation criteria cannot be answered from this document.

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