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The BiZact™ device is a bipolar instrument intended for use in open surgical procedures where ligation and division of vessels, tissue bundles, and lymphatics is desired.

The tissue fusion function of the device can be used on vessels (arteries and veins) and lymphatics up to and including 3 mm diameter. The BiZact device is indicated for use in open general surgical procedures.

It is also indicated for adult ENT procedures, including tonsillectomy for the ligation and division of vessels, tissue bundles and lymphatics 2-3 mm away from unintended thermally sensitive structures.

The BiZact™ device has not been shown to be effective for tubal sterilization or tubal coagulation for sterilization procedures. Do not use for these procedures.

The BiZact™ Tonsillectomy Device Advanced Bipolar Tissue Sealer/Divider is a sterile, single use, hand-held electrosurgical device that incorporates RF tissue fusion technology for a desired tissue effect when used with the ForceTriad Energy Platform (K051644, K070162, K102913, and K110268), the Valleylab™ LS10 LS Series Single Channel Vessel Sealing Generator (K143654), or the Valleylab FT10 Energy Platform (K151649, K170170) for ligation and division of vessels, tissue bundles, and lymphatics during open general surgical procedures.

The BiZact™ Tonsillectomy Device Advanced Bipolar Tissue Sealer/Divider attaches to a compatible electrosurgical generator with a 10 foot cord containing a proprietary connector. The generator is able to identify the BiZact™ device via the RFID tag embedded in the connector (Valleylab LS10 LS Series single Channel Vessel Sealing Generator and Valleylab FT10 Electrosurgical Platform) or with a barcode on the connector (ForceTriad). The generator delivers energy to the device using a defined algorithm that adjusts the generator output as a function of the electrical resistance of the combination of the BiZact instrument and the generator algorithm achieve complete and permanent tissue fusion.

The provided document is a 510(k) premarket notification for a medical device (BiZact Tonsillectomy Device) and does not contain information about an AI/ML-based device or its performance criteria related to AI/ML tasks.

Therefore, I cannot extract the requested information regarding acceptance criteria and study details for an AI/ML device's performance. The document focuses on the substantial equivalence of a physical electrosurgical device to a predicate device, based on mechanical, electrical, functional, biocompatibility, sterilization, and animal (ex-vivo/in-vivo) studies.

The request asks for:

1. Table of acceptance criteria and reported device performance (for AI/ML): Not applicable, as this is not an AI/ML device. The document summarizes various engineering and biological tests, but not specific AI performance metrics like sensitivity, specificity, or AUC.
2. Sample size for test set and data provenance: The document mentions "fresh porcine renal arteries" for burst pressure, "porcine model" for lymphatic and acute hemostasis studies, and a "chronic hemostasis porcine study." It does not specify sample sizes in terms of number of cases for these animal studies beyond indicating they were sufficient for verification. Data provenance is "porcine model" (animal data), which is prospective in the context of these experiments. There is no human patient data test set for AI.
3. Number of experts and qualifications for ground truth: Not applicable for an AI/ML device. Ground truth in this context would be physical measurements, biological response, or pathological findings from the animal studies, not expert consensus on AI outputs.
4. Adjudication method: Not applicable for an AI/ML device.
5. MRMC comparative effectiveness study: Not applicable, as there's no AI component or human reader interaction with AI.
6. Standalone AI performance: Not applicable.
7. Type of ground truth: For the physical device, it's based on physiological and pathological outcomes in animal models (e.g., vessel burst pressure, acute hemostasis, lymphatic sealing, lateral thermal spread over time).
8. Sample size for training set: Not applicable, as there is no AI training set.
9. How ground truth for training set was established: Not applicable.

In summary, the provided document describes a medical device clearance for an electrosurgical tool, not an AI/ML device. Therefore, none of the requested information pertaining to AI/ML acceptance criteria and performance studies can be found or inferred from the text.

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