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The T.B.R.® ide@ conic endosseous dental implant is a device intended to be surgically placed in the bone of the upper or lower jaw arches to provide support for prosthetic devices, such as artificial teeth, and to restore the patient's chewing function.

Description of the donic/Conic dental implant system consists of selftapping threaded screw-type implants (made from Ti-6AI-4V ) and tapping througou overs with many options such as Ti-6Al-4V abutments, tapered abutments, castable abutments, ball abutments and ceramic/Titapered abutments. The system also include surgical and laboratory ord av abutiments. Implants are double-packaged and provided sterile. Implants surface is roughened to promote osseointegration.

The provided document is a 510(k) summary for a medical device (T.B.R.® ide@ conic endosseous dental implant) and does not describe acceptance criteria or a study that proves the device meets those criteria in the context of an AI/ML algorithm.

Instead, the document focuses on demonstrating substantial equivalence to predicate devices based on:

1. Mechanical testing: This was done in accordance with FDA guidance for root-form endosseous dental implants and abutments. It showed "sufficient mechanical static and dynamic strength."
2. Biocompatibility testing: Conclusions demonstrate the safety and effectiveness of the implant system.
3. Technological characteristics: A comparison table is provided highlighting similarities in type, lengths, diameters, connection, shape, materials, and surface with predicate devices.

Therefore, I cannot provide the requested information for an AI/ML device's acceptance criteria and study, as the input document describes a traditional medical device (dental implant).

The following information cannot be extracted from the provided document as it pertains to a traditional medical device submission, not an AI/ML device:

1. A table of acceptance criteria and the reported device performance (for an AI/ML algorithm).
2. Sample size used for the test set and the data provenance.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts.
4. Adjudication method for the test set.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and its effect size.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done.
7. The type of ground truth used.
8. The sample size for the training set.
9. How the ground truth for the training set was established.

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