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The Tri-Staple 2.0 Reinforced Reload with polyglycolic acid staple line reinforcement has applications in abdominal, gynecologic, pediatric and thoracic surgery for resection of tissue and creation of anastomosis. They may be used for transection of liver substance, hepatic vasculature and biliary structures, and for transection and resection of pancreas.

The Tri-Staple™ 2.0 reinforced reload places two triple- staggered rows of titanium staples and two layers of absorbable reinforcement material on either side of the cut line. The absorbable staple line reinforcement material, comprised of a synthetic polyester composed of pure glycolide, will be secured to the anvil and cartridge sides of the reload with four synthetic absorbable sutures. As the staples are deployed, the tissue and staple line reinforcement material are simultaneously divided. The Tri-Staple™ 2.0 reinforced reload is available in articulating 45 mm and 60 mm lengths. The size of the staples is determined by the selection of the 3.0-4.0mm or 4.0-5.0mm reload. The Tri-Staple™ 2.0 reinforced reload will contain an intelligence chip. The intelligence chip will have the ability to communicate with Covidien™ powered stapling handles that have a compatible communications interface.

The provided text describes a 510(k) premarket notification for a medical device, the Tri-Staple 2.0 Reinforced Reload. It outlines the device's intended use, technological characteristics, and various performance tests conducted to demonstrate substantial equivalence to a predicate device.

However, the document does not contain the specific information requested in your prompt regarding acceptance criteria and a study proving the device meets them, especially in the context of AI/ML performance. Your request asks for details like:

• A table of acceptance criteria and reported device performance.
• Sample size and data provenance for a test set.
• Number and qualifications of experts for ground truth.
• Adjudication method for the test set.
• MRMC comparative effectiveness study results (AI vs. without AI).
• Standalone algorithm performance.
• Type of ground truth used.
• Training set sample size and ground truth establishment.

The provided text focuses on the regulatory submission for a surgical stapler and its sterile reload, which is a physical medical device, not an AI/ML-driven diagnostic or assistive tool. The performance data mentioned (e.g., staple formation, blood loss, air leak evaluation) are related to the mechanical and biological function of the stapler in surgical procedures.

Therefore, I cannot provide the requested information from the given text because it does not pertain to an AI/ML device that would require such specific performance metrics and study designs related to AI model evaluation.

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