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All indications for displacement of the marginal gingiva and to provide for a dry sulcus when the periodontium is healthy.

CoSP2, manufactured by 3M ESPE, is a retraction paste for the displacement of marginal gingiva and to provide for a dry sulcus. Any suitable, commonly available dispensers, e.g., the Capsule Applicator, manufactured for 3M ESPE, can be used for application of the retraction paste. The paste is applied directly from the retraction capsule into the sulcus. A CoSP2 retraction capsule may not be used on more than one patient.

I am sorry, but based on the provided text, there is no information about a study that proves the device meets specific acceptance criteria in the way you've outlined for AI/ML device evaluation.

The provided document is a 510(k) summary for a medical device called "CoSP2," which is a retraction paste used in dentistry. The document focuses on demonstrating substantial equivalence to predicate devices, not on proving performance against a set of quantitative acceptance criteria through a specific performance study as would be typical for an AI/ML device.

Here's why I cannot fulfill your request based on the given text:

• Type of Device: CoSP2 is a physical dental paste, not an AI/ML device or software. Therefore, the evaluation methodology and criteria are fundamentally different.
• Safety and Effectiveness Claims: The document states, "In this 510(k) premarket notification chemical composition, performance data (e.g. extrusion force, flow resistance, and rinsing time), and indications for use of CoSP2 have been compared to its predicate devices." and "To provide evidence for safety biocompatibility testing was carried out. The results show that CoSP2 is a safe device." It concludes: "In summary, it can be concluded that safety and effectiveness requirements for CoSP2 are completely met."
• "Performance Data" Context: The "performance data" mentioned (extrusion force, flow resistance, and rinsing time) are physical properties of the paste, not clinical efficacy or diagnostic accuracy metrics related to AI.
• No "Acceptance Criteria" Table: There is no table of acceptance criteria or reported device performance metrics in the way you've requested (e.g., sensitivity, specificity, AUC) for an AI/ML device.
• No ML-Specific Study Information: The document does not mention anything about:
  • Sample sizes for test sets (beyond general product testing).
  • Data provenance for clinical images/data.
  • Number or qualifications of experts establishing ground truth.
  • Adjudication methods.
  • Multi-reader multi-case (MRMC) studies or comparative effectiveness with human readers.
  • Standalone AI algorithm performance.
  • Types of ground truth (e.g., pathology, outcomes data).
  • Training set sample size or how its ground truth was established.

In essence, the 510(k) submission for CoSP2 focuses on demonstrating that the device is as safe and effective as existing legally marketed predicate devices, primarily through comparison of chemical composition, physical performance characteristics, and biocompatibility testing. It doesn't involve the kind of performance study or acceptance criteria relevant to an AI/ML diagnostic or assistive device.

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