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The Ciba Corning 400 System is intended for the point-of-care and laboratory testing of blood gases, electrolytes and metabolites in arterial, venous and capillary whole blood samples.

The 400 Series system analyzer is a point of care and laboratory testing analyzer used to for the direct measure of whole blood samples for the determination of the following parameters:

• partial pressures of carbon dioxide; pCO2
• partial pressure of oxygen pO2
• pH
• sodium; Na*
• potassium: K*
• ionized calcium; Ca**
• chloride: Cli
• alucose
• hematocrit: Hct

The provided text describes a medical device, the Ciba Corning 400 System, an analyzer for blood gases, electrolytes, and metabolites. It details the device's function, intended use, and technological characteristics. However, it does not contain the acceptance criteria or a study proving the device meets said criteria.

Therefore, I cannot provide the requested information, particularly:

• A table of acceptance criteria and reported device performance: This information is not present in the document.
• Sample sized used for the test set and the data provenance: There is no mention of a test set or its sample size or origin.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Ground truth establishment for a test set is not discussed.
• Adjudication method for the test set: No test set or adjudication is mentioned.
• 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: This document predates widespread AI in medical devices and does not describe such a study.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: No such study is mentioned.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc): Ground truth is not discussed in the context of device performance validation.
• The sample size for the training set: There is no mention of a training set as this is not an AI/ML device.
• How the ground truth for the training set was established: Not applicable, as there's no training set mentioned.

The document is a "Summary of Safety and Effectiveness" from 1996 for a 510(k) submission, focusing on describing the device, its predicate, and its measurement technology. It doesn't include the detailed performance study results and acceptance criteria typically found in more extensive validation reports.

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