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The Bak'Snap DuoProSS™ Retractable Safety Syringe is a sterile, single-use, disposable and non-reusable, manual, retractable safety syringe intended for injection of fluids into the body, while reducing the risk of sharps injuries and the potential for syringc reuse.

The 10 mL Bak'Snap DuoProSS™ Retractable Safety Syringe is a sterile, single-use, disposable and non-rcusable, manual, retractable safety syringe provided with or without needle. The modifications to the cleared product are the addition of a brand name, a change in syringe volume, and a change in a single syringe material.

The provided document is a 510(k) summary for a medical device (10 mL Bak'Snap DuoProSS™ Retractable Safety Syringe), which focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study proving performance against acceptance criteria in the context of an AI/algorithm-based device.

Therefore, most of the requested information regarding acceptance criteria, study design, expert involvement, and ground truth for an AI device is not available in these documents. The document describes a traditional medical device (a syringe), not an algorithm or AI product.

Here's an attempt to address the prompts based only on the provided text, recognizing that it pertains to a physical device and not an AI algorithm:

Based on the provided K034031 510(k) Summary for the 10 mL Bak'Snap DuoProSS™ Safety Syringe, the detailed information typically required for an AI/algorithm-based device's acceptance criteria and proving study is not present. This document describes a traditional medical device (a syringe) and its substantial equivalence to a predicate device, rather than the performance of a diagnostic or predictive algorithm.

However, I can extract information related to the device's functional intent and general testing performed.

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

The document does not explicitly list quantitative acceptance criteria in terms of performance metrics (like sensitivity, specificity, AUC) for an AI device, nor does it report specific performance values in that context. Instead, it focuses on demonstrating substantial equivalence based on intended use, design, and technological/operational characteristics, and conformance to standards.

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

Not applicable. The document refers to "verification and validation testing" but does not specify sample sizes for specific tests or the provenance of any 'data' in the context of an algorithm's test set. This is a physical device, and testing would involve physical samples, not a data test set for an algorithm.

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 information is relevant for AI/algorithm validation, not for the substantial equivalence demonstration of a physical medical device like a syringe.

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

Not applicable. This is typically used for resolving discrepancies in expert labeling or ground truth establishment for AI models.

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 study type is for evaluating the impact of AI on human performance, and this document pertains to a physical syringe, not an AI system.

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

Not applicable. This concept applies to the performance of an AI algorithm in isolation.

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

Not applicable in the context of an AI algorithm's ground truth. For a physical device like a syringe, "ground truth" would relate to whether the device meets its functional specifications and safety requirements (e.g., sterility, non-reusability, physical dimensions, retraction mechanism function), likely assessed through engineering tests and adherence to standards.

8. The sample size for the training set

Not applicable. This device is not an AI algorithm that requires a training set.

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

Not applicable. This information pertains to AI model development.

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