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The Merit Hydrophilic Guide Wire is intended to be used in the peripheral vascular system to facilitate the placement of devices during diagnostic and interventional procedures.

The Merit Hydrophilic Guide Wire consists of a jacketed core wire with a hydrophilic coating applied to the jacket. The wire will be offered in straight and angled configurations in various lengths.

The provided text refers to a medical device, the "Merit Hydrophilic Guide Wire," and its substantial equivalence to predicate devices, rather than an AI/ML powered device. Therefore, many of the requested details about acceptance criteria, study design, and ground truth for an AI/ML model are not applicable.

However, I can extract information related to the device's performance testing and how it met acceptance criteria for substantial equivalence to predicate devices.

Summary of Acceptance Criteria and Device Performance (for the Merit Hydrophilic Guide Wire):

Study Information (Based on Substantial Equivalence Evaluation):

1. Sample sizes used for the test set and data provenance:
   This information is not provided in a way that is applicable to an AI/ML model. The "test set" in this context refers to a series of physical tests performed on the guide wire samples. The document does not specify the number of guide wires tested for each attribute or their provenance. The "data provenance" mentioned in your request (country of origin of data, retrospective/prospective) is relevant for clinical data, not for material property testing of a medical device.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
   Not applicable. "Ground truth" in this context would typically refer to expert consensus on clinical diagnoses for AI/ML. For a physical device, testing against defined engineering specifications serves as the "ground truth." The document states "protocols based on requirements outlined in guidance's and industry standards," implying established engineering and scientific methods rather than expert clinical consensus on individual test results.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
   Not applicable. Adjudication methods like 2+1 or 3+1 are used for resolving disagreements among multiple human readers in clinical studies, particularly for AI/ML evaluation. This document describes laboratory testing against established standards.

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, as this is not an AI/ML device.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
   Not applicable, as this is not an AI/ML device.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
   For this medical device, the "ground truth" for the performance tests was established by industry standards (e.g., ISO 11070:1998, ISO 11135-1:2007, ASTM F1980-07, ISO 10993-1:2009) and FDA guidance (Coronary and Cerebrovascular Guide Wire Guidance January 1995, FDA Modified ISO 10993 Test Profile FDA Memo G95-1). The device's performance was compared to a "predicate device" (Terumo Radiofocus® Glidewire® K863138) for various attributes.

7. The sample size for the training set:
   Not applicable, as this is not an AI/ML device, and therefore no "training set" in that sense was used. The device underwent physical and chemical testing.

8. How the ground truth for the training set was established:
   Not applicable, as this is not an AI/ML device.

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