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The Focus Cap has been designed to be attached to the distal end of a colonoscope. The Focus Cap is intended for the following:

• For use in keeping the suitable depth of the colonoscope's field of view.

The GCE Focus Cap has the shape of a short transparent tube which is attached to the distal end of the colonoscope. The Focus Cap is designed to facilitate the scope's view during colonoscopy procedures.

The provided text describes a 510(k) premarket notification for the "Focus Cap" device. This document does not describe a study that uses acceptance criteria for algorithm performance in the way typically seen for AI/ML devices. Instead, it focuses on demonstrating substantial equivalence to a predicate device through performance testing related to mechanical and biocompatibility aspects of the physical device.

Therefore, many of the requested categories are not applicable to the information contained in this document.

Here's a breakdown based on the provided text:

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

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

This information is not provided in the document. The document refers to "test protocols," but does not detail the sample sizes or provenance for the mechanical and biocompatibility testing.

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)

Not applicable. This document is for a physical medical device (a cap for a colonoscope), not an AI/ML device that requires expert-established ground truth for its performance in a clinical task.

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

Not applicable. This document is for a physical medical device and does not involve adjudication of 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 is for a physical medical device and does not involve AI assistance or human reader performance.

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

Not applicable. This is a physical device, not an algorithm.

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

For mechanical and biocompatibility testing, the "ground truth" would be established by standardized testing methods and material specifications, not expert clinical consensus or pathology. The document states "All test requirements were met as specified by test protocols and pre-determined acceptance criteria."

8. The sample size for the training set

Not applicable. This document is for a physical device, not an AI/ML model with a training set.

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

Not applicable. This document is for a physical device, not an AI/ML model with a training set.

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