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The device is a personal lubricant, for penile and/or vaginal application, intended to moisturize and lubricate, to enhance the ease and comfort of intimate sexual activity, and supplement the body's natural lubrication. This product is compatible with polyisoprene condoms. This device is not compatible with natural rubber latex or polyurethane condoms.

Internal Hydrating Gel is a colorless, transparent, aqueous, hydrating gel in tube with 8 syringes for easy application. Internal Hydrating Gel is intended for use as a personal lubricant. This product is compatible with polyisoprene condoms. This device is not compatible with natural rubber latex or polyurethane condoms. Accordingly, the following parameters are included as part of the product specification: Appearance, Color, Odor, pH, Viscosity, Osmolality, Antimicrobial effectiveness, Total Aerobic Microbial Count (TAMC), Total Yeast and Mold Count (TYMC), Absence of Pathogenic Organisms (at minimum Pseudomonas aeruginosa, Staphylococcus aureus, and Candida albicans). Internal Hydrating Gel has a pH of 4.5-5.0 and a shelf life of 21 months.

This document is a 510(k) summary for the "Internal Hydrating Gel," a personal lubricant. It doesn't contain a detailed study proving the device meets specific acceptance criteria in the way a clinical performance study for an AI/ML device would. Instead, it relies on demonstrating substantial equivalence to a predicate device through various tests.

Therefore, many of the requested fields cannot be directly answered from the provided text as this is not a study on an AI device. However, I can extract the relevant information on reported device performance and the tests performed to support safety and equivalence.

Here's the breakdown based on the provided text, focusing on the closest equivalents to your request:

1. Table of Acceptance Criteria and Reported Device Performance

This document describes the product specifications and the results of various testing conducted to demonstrate safety and substantial equivalence to a predicate device. It doesn't present "acceptance criteria" in the traditional sense of a clinical performance study with defined thresholds for sensitivity, specificity, etc., nor a comparison to an AI/ML algorithm's output. Instead, it lists physical/chemical properties and biological safety tests.

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

• Sample size for test set: Not specified in the document. The types of tests (e.g., biocompatibility) would involve specific sample sizes per test, but these are not detailed.
• Data provenance: Not specified. Standard pre-clinical and clinical testing for medical devices typically adheres to international guidelines (e.g., ISO for biocompatibility) but the specific origin cannot be determined from this summary. It's prospective testing.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• This question is not applicable as this is not an AI/ML device study. Ground truth in this context would refer to objective measurements and expert evaluation in the various tests (e.g., laboratory technicians for microbial counts, toxicologists for biocompatibility assessments, clinical dermatologists for HRIPT, etc.), but explicitly stated expert numbers or qualifications are not provided.

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

• Not applicable as this is not a study comparing interpretations, such as in an imaging study.

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 is not an AI/ML device; therefore, no MRMC study with AI assistance was performed.

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

• Not applicable. This is not an AI/ML device; there is no algorithm, and therefore no standalone performance study was done.

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

• "Ground truth" in this context refers to the results of established scientific and laboratory testing methods (e.g., pH meters, viscometers, microbiological culture results, toxicity assays according to ISO standards, clinical observations for irritation). It is based on objective measurements and standardized test protocols rather than expert consensus on, for instance, image interpretation.

8. The sample size for the training set

• Not applicable. This is not an AI/ML device; there is no training set.

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

• Not applicable. This is not an AI/ML device; there is no training set or associated ground truth.

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