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The cobas® liat SARS-CoV-2 v2 nucleic acid test is an automated real-time reverse transcription polymerase chain reaction (RT-PCR) test intended for the qualitative detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acids in anterior nasal (nasal) and nasopharyngeal swab specimens collected from individuals exhibiting signs and symptoms of respiratory tract infection (i.e., symptomatic). Additionally, this test is intended to be used with nasal and nasopharyngeal swab specimens collected from individuals without signs and symptoms of COVID-19 (i.e., asymptomatic).

The cobas® liat SARS-CoV-2 v2 nucleic acid test is intended for use as an aid in the diagnosis of COVID-19 if used in conjunction with other clinical and epidemiological information and laboratory findings. SARS-CoV-2 RNA is generally detectable in nasal swab and nasopharyngeal swab specimens during the acute phase of infection.

Positive results are indicative of the presence of SARS-CoV-2 RNA. Positive results do not rule out co-infection with other microorganisms. Negative results do not preclude SARS-CoV-2 infection. Negative results must be combined with clinical observations, patient history, and epidemiological information. The results of this test should not be used as the sole basis for diagnosis, treatment, or other patient management decisions.

A negative result from an asymptomatic individual is presumptive. Additionally, a negative result obtained with a nasal or nasopharyngeal swab collected from an asymptomatic individual should be followed up by testing at least twice over three days with at least 48 hours between tests.

The cobas® liat SARS-CoV-2 v2 nucleic acid test is performed on the cobas® liat analyzer which automates and integrates sample purification, nucleic acid amplification, and detection of the target sequence in biological samples using real-time PCR assays. The assay targets both the ORF1 a/b non-structural region and membrane protein gene that are unique to SARS-CoV-2. An Internal Control (IC) is included to control for adequate processing of the target virus through all steps of the assay process and to monitor the presence of inhibitors in the RT-PCR processes.

The provided text is a 510(k) Clearance Letter for a medical device which does not include information about AI/ML models. Therefore, it's not possible to extract the information you requested about Acceptance Criteria and a study proving an AI/ML device meets those criteria.

The device described, the "cobas liat SARS-CoV-2 v2 nucleic acid test," is an in vitro diagnostic (IVD) device based on real-time RT-PCR technology. It directly detects viral targets and its performance is evaluated through analytical and clinical studies common for IVDs, not against AI/ML performance metrics like sensitivity, specificity, MRMC studies, or multi-reader reviews.

Here's a breakdown of why your requested information isn't present in this document:

• No AI/ML Component: The document describes a traditional RT-PCR assay. There is no mention of algorithms, machine learning, deep learning, or any AI component.
• Performance Metrics Differ: The performance metrics provided (Limit of Detection, Inclusivity, Cross-reactivity, Reproducibility, Positive Percent Agreement, Negative Percent Agreement) are standard for IVD assays. They are not analogous to metrics used for evaluating AI/ML models (e.g., AUC, F1-score, accuracy in image classification, or diagnostic improvement from AI-assistance).
• No Human Reader Interaction: Since it's an automated lab test, there's no "human reader" (like a radiologist) involved in interpreting the device's output in a way that an AI would assist. The output is qualitative (Detected/Not Detected).
• No Ground Truth Experts in the AI Sense: Ground truth for this IVD is established by a "comparator" (another FDA-cleared NAAT) and clinical/epidemiological information, not by multiple human experts reviewing AI outputs or images.
• No Training/Test Set Split for AI: The "test set" and "training set" concepts described in your request are fundamental to AI/ML model development and validation. For this IVD, there's a "clinical performance evaluation" using prospective and retrospective samples, which serves as the validation dataset, but it's not structured as a training/test split for an AI.

Therefore, I cannot provide the requested table and detailed points because the provided document does not pertain to an AI/ML device.

If you have a document describing an AI/ML medical device, please provide that, and I can attempt to extract the relevant information.

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