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The NeoBase™ 2 Non-derivatized MSMS kit is intended for the measurement and evaluation of amino acid, succinylacetone, free carnitine, acylcarnitine, nucleoside and lysophospholipid concentrations (Table 1) with a tandem mass spectrometer from newborn heel prick blood specimens dried on filter paper. Quantitative analytes and their relationship with each other is intended to provide analyte concentration profiles that may aid in screening newborns for metabolic disorders.

Each NeoBase 2 Non-derivatized MSMS kit contains reagents for 960 assays. The kit is designed to be used with NeoBase 2 Non-derivatized Assay Solutions consisting of Neo MSMS Flow Solvent and NeoBase 2 Extraction Solution and NeoBase 2 Succinylacetone Assay Solution.

• NeoBase 2 Internal Standards - 1 vial
• NeoBase 2 Controls Low, High - 3 filter paper cassettes (Whatman, no. 903) containing 3 spots of each level per cassette
• Microplate, U-bottomed - 20 plates
• Adhesive microplate covers - 20 sheets
• Barcode labels for the plates - 30 pcs (10 different barcodes, 3 pcs of each)
• Lot-specific quality control certificate
  This kit contains components manufactured from human blood. The source materials have been tested by FDA-approved methods for hepatitis B surface antigen, anti-hepatitis C and anti-HIV 1 and 2 antibodies and found to be negative.
  Instruments used:
• . QSight® 210 MD Screening System is comprised of:
  • QSight® 210 MD Mass Spectrometer
  • QSight® HC Autosampler MD
  • QSight® Binary Pump MD ●
  • Simplicity™ 3Q MD Software
• PerkinElmer MSMS Workstation software ●

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text.

Note: This document describes a medical device for newborn screening. Performance is demonstrated through analytical studies (precision, sensitivity, linearity, interference) and screening performance data comparing it to a predicate device, rather than human-in-the-loop studies common for AI/imaging devices. Thus, several sections typically relevant to AI-based devices (e.g., number of experts, adjudication methods, MRMC studies) are not applicable here.

Acceptance Criteria and Device Performance

The acceptance criteria for the NeoBase 2 Non-derivatized MSMS kit are implied by the comprehensive analytical and screening performance evaluation studies conducted. The goal is to demonstrate that the device performs equivalently to the legally marketed predicate device (NeoBase 2 Non-derivatized MSMS kit, K173568) and provides reliable results for newborn screening.

The reported device performance below highlights key analytical and screening metrics. Specific numerical acceptance criteria are not explicitly stated as hard thresholds (e.g., "CV must be < X%"), but rather the results of the studies are presented to demonstrate acceptable performance comparable to a cleared predicate.

Table of Acceptance Criteria (Implied) and Reported Device Performance

Study Details

1. Sample Size and Data Provenance:

   • Test Set (Screening Performance): 2530 routine newborn screening specimens.
     • Country of Origin: United States (one routine screening laboratory in the US).
     • Retrospective/Prospective: The nature of "routine screening specimens" usually implies retrospective use of collected samples for evaluating a new method, but explicit detail (e.g., prospective collection specifically for this study) is not given. However, the study focuses on comparing the new device (QSight) to the predicate (TQD) on these samples, suggesting an evaluation of existing data or new data collected in a routine setting.
   • Analytical Studies (Precision, Linearity, Interference):
     • Precision: 80 determinations (40 plates x 2 replicates) for repeatability and within-laboratory; 75 determinations (15 plates x 5 replicates x 3 lots) for between-lot; 50 determinations (10 plates x 5 replicates x 2 QSights) for between-instrument.
     • Reproducibility: 75 determinations (5 plates x 5 working days x 5 replicates) across 3 labs (1 internal, 2 external).
     • Linearity, Sensitivity, Interference: Not explicitly quantified by sample size in the same way as precision. These studies typically use a controlled set of samples spiked with known concentrations or interfering substances.

2. Number of Experts and Qualifications for Ground Truth:

   • This device is a quantitative assay for measuring analyte concentrations, not an AI/imaging device requiring expert interpretation of images.
   • The "ground truth" for the screening performance study are confirmed positive specimens for various metabolic disorders (Amino Acid, Fatty Acid Oxidation, Organic Acid, ADA-SCID, X-ALD). These confirmations are typically established through gold standard clinical diagnostic methods (e.g., genetic testing, enzyme assays, or further biochemical analysis), not through expert panel review of the screening test results themselves. The document states "confirmed positive specimens," implying these are definitive diagnoses.
   • Therefore, the concept of "experts" establishing ground truth for the test set, in the way a radiologist reads an image, does not directly apply here.

3. Adjudication Method for the Test Set:

   • Not applicable as this is a quantitative diagnostic assay. "Adjudication" typically refers to resolving disagreements among human readers/interpreters, which is not the primary function of this device or study design. The study compares the new device's quantitative results and detection rates against those of a predicate device and known confirmed positive cases.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • Not applicable. This is not a study comparing human readers with and without AI assistance. It is a comparison of two analytical instruments/kits (the new NeoBase 2 on QSight vs. predicate NeoBase 2 on TQD).

5. Standalone Performance (Algorithm-only without human-in-the-loop):

   • Yes, this study is a standalone performance evaluation. The device (NeoBase 2 kit run on QSight MD Screening System) provides quantitative measurements of analytes. The performance tables directly show the device's analytical capabilities (precision, sensitivity, linearity, reproducibility) and its ability to detect known positive cases in a patient population without human interpretation as part of the core measurement. Human expert judgment comes in for confirming the disease in patient specimens (the ground truth), but not in interpreting the raw output of the device itself.

6. Type of Ground Truth Used:

   • Confirmed positive specimens: For the screening performance study, the ground truth was based on specimens from individuals clinically confirmed to have the targeted metabolic disorders (Amino Acid Disorders, Fatty Acid Oxidation, Organic Acid Conditions, ADA-SCID, X-ALD). This likely involved definitive diagnostic tests beyond initial screening, such as genetic testing, enzyme activity assays, or more specific quantitative metabolite analysis. This is a form of outcomes data/definitive diagnosis.

7. Sample Size for the Training Set:

   • This is a medical device for quantitative measurement, not a machine learning or AI model that requires a "training set" in the conventional sense (i.e., data used to teach an algorithm to learn patterns). The device's performance validation relies on analytical studies to demonstrate its accuracy, precision, and consistency, and then clinical performance by comparing its results to a predicate device and confirmed clinical cases. Therefore, the concept of a training set as understood in AI/ML is not relevant here.

8. How Ground Truth for the Training Set Was Established:

   • Not applicable, as there is no "training set" in the context of an AI/ML model for this type of device. The device's performance is intrinsically linked to its chemical reagents and mass spectrometry technology, which are developed and calibrated through standard analytical chemistry procedures.

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The NeoBase™ 2 Non-derivatized MSMS kit is intended for the measurement and evaluation of amino acid, succinylacetone, free carnitine, acylcarnitine, nucleoside and lysophospholipid concentrations (Table 1) with a tandem mass spectrometer from newborn heel prick blood specimens dried on filter paper. Quantitative analytis of these analytes and their relationship with each other is intended to provide analyte concentration profiles that may aid in screening newborns for metabolic disorders.

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The provided text describes the acceptance criteria and study results for the NeoBase 2 Non-derivatized MSMS kit.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria for the screening performance studies (e.g., minimum sensitivity or specificity targets). Instead, it states that "All verification studies were successfully concluded and met the respective study's predetermined acceptance criteria." The clinical studies for screening performance are presented as agreement between the new device (NeoBase 2) and the predicate device (NeoBase). The agreement is presented as contingency tables (e.g., "Screening positive" vs "Screening negative" for both devices).

The performance is demonstrated by the agreement between the NeoBase 2 Non-derivatized MSMS kit and the predicate device, NeoBase Non-derivatized MSMS kit, in detecting various metabolic disorders in newborn screening. The results are presented in terms of the number of positive and negative screens detected by each device, along with the number of confirmed positive specimens.

Summary of Device Performance (from Tables A, B, C, D):

2. Sample Size Used for the Test Set and Data Provenance

• Study 1 Sample Size:

  • Amino acid disorders, Fatty acid oxidation, Organic acid conditions: 1751 samples (for 99th and 99.5th percentile cut-offs) and 1737-1746 samples (for 1st and low percentile cut-offs).
  • ADA-SCID and X-ALD: 1738 samples.

• Study 2 Sample Size:

  • Amino acid disorders, Fatty acid oxidation, Organic acid conditions: 2631-2648 samples.
  • ADA-SCID and X-ALD: 2631 samples.

• Data Provenance: The data was obtained from "routine newborn screening" in "two CLIA-certified state laboratories." The confirmed positive specimens were described as "retrospective" for Study 2. This suggests a retrospective study design using existing samples and accompanying diagnostic information. The country of origin is not explicitly stated but is implied to be the US due to "CLIA-certified state laboratories."

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

The document does not specify the number or qualifications of experts used to establish the ground truth for the test set. It mentions "confirmed positive specimens," implying a definitive diagnostic process was followed to establish the true disease status of these samples, but details on the experts involved are not provided.

4. Adjudication Method for the Test Set

The document does not describe an adjudication method for the test set, such as 2+1 or 3+1. The acceptance is based on the agreement between the new device and the predicate device, using established cut-offs derived from routine newborn screening data.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No MRMC comparative effectiveness study was done. This device is a diagnostic kit measuring analyte concentrations, not an AI system assisting human readers. Therefore, the concept of "how much human readers improve with AI vs without AI assistance" is not applicable.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

The study described is a comparison of the new device (NeoBase 2) to a predicate device (NeoBase) in obtaining analyte concentrations. While not explicitly stated as an "algorithm only" study, it's a standalone performance comparison of two test kits. The results (analyte concentrations and screening positive/negative classifications) are derived directly from the kit's operation with a tandem mass spectrometer, without human interpretation being part of the primary measurement process itself. The interpretation of the analyte profiles to aid in screening for metabolic disorders would typically involve medical professionals, but the performance data presented is on the analytical and classification output of the device.

7. Type of Ground Truth Used

The ground truth for the test set was based on "confirmed positive specimens." This implies that the true disease status of these specimens was established through clinical diagnosis and follow-up, which would typically involve a combination of clinical outcomes, biochemical testing, and/or genetic testing, ultimately confirmed by clinical experts. For ADA-SCID and X-ALD, it explicitly states "comparing the result... to the clinical condition."

8. Sample Size for the Training Set

The document does not explicitly mention a "training set" in the context of machine learning or AI. The term "cut-offs for both methods were determined by calculating the 99.5th and 99th percentile for all analytes" using "data from routine newborn screening." This large volume of routine newborn screening data could be considered analogous to a training or reference population used to establish the operating characteristics of the screening test. The specific sample size for this cut-off determination is not given, but it is implied to be a large dataset from the "two CLIA-certified state laboratories."

9. How the Ground Truth for the Training Set Was Established

As discussed in point 8, there isn't a traditional "training set" for an AI model. However, the cut-off values (e.g., 99th, 99.5th, 1st, 10th percentiles) used to define "screening positive" or "screening negative" were established using "data from routine newborn screening." This means the ground truth for establishing these cut-offs would inherently come from the statistical distribution of analyte levels in a large, presumably healthy and general newborn population, along with the understanding of what analyte levels are indicative of various metabolic disorders. The document states that the cut-off values "only apply to these studies."

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The Neobase Non-derivatized MSMS reagent kit (for use on the PerkinElmer TQD MSMS Screening System) is intended for the measurement and evaluation of amino acids, succinylacetone, free carnitine, and acylcarnitine concentrations from newborn heel prick blood samples dried on filter paper. Quantitative analysis of these analytes (Table 1) and their relationship with each other is intended to provide analyte concentration profiles that may aid in screening newborns for metabolic disorders.

The measurement of amino acids, succinylacetone, free carnitine, and acylcarnitines with the NeoBase assay involves extraction of dried blood spots from newborns with a solution containing stable-isotope labeled internal standards and analysis using a tandem mass spectrometry (MSMS) system. The each analyte relative to their response of internal stable-isotope labeled corresponding standard is proportional to analyte concentration.

The device being described is the NeoBase Non-derivatized MSMS Kit, intended for the measurement and evaluation of amino acid, succinylacetone, free carnitine, and acylcarnitine concentrations from newborn heel prick blood samples dried on filter paper. This quantitative analysis aids in screening newborns for metabolic disorders.
The study presented is a non-clinical study comparing the performance of the NeoBase Non-derivatized MSMS kit on the PerkinElmer TQD Triple Quadrupole Mass Spectrometer System (PerkinElmer TQD platform) against its predicate devices, the MS2 and PerkinElmer Quattro Micro platforms (QMicro). The goal was to demonstrate substantial equivalence.

Here's the breakdown of the acceptance criteria and study information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" as a set of predefined thresholds. Instead, it demonstrates equivalence to predicate devices by showing comparable performance characteristics. The key performance metrics evaluated were:

• Precision (Imprecision Percent Coefficient of Variation - %CV): Lower %CV indicates higher precision.
• Recovery (Mean % Recovery and 95% Confidence Interval): Indicates the accuracy of analyte measurement.
• Measurable Ranges: The range over which the device can accurately quantify analytes, ensuring coverage of clinically significant levels.
• Method Correlation (Ratio of Measured Concentration): Comparing the TQD platform with predicate devices (MS2 and QMicro). A ratio of 1.0 indicates equivalent concentration measurements.
• Clinical Correlation (Percent Agreement in clinical determinations): How well the TQD platform agrees with predicate platforms in classifying samples above or below clinical cutoffs.
• Detection of True Positive Samples: The ability of the device to correctly identify known positive cases.

Here's a summary of the reported device performance, focusing on the TQD platform's comparison to predicate devices:

2. Sample Size Used for the Test Set and Data Provenance

• Non-clinical (Analytical) Test Set:
  • Precision and Recovery: The tables provided (5.3, 5.4, 5.5) show averaged data, but the explicit number of samples/replicates isn't detailed for each specific test. However, the method correlation section states that "enriched samples (five levels) was analyzed (as singlicates of each level) for 16 runs to provide a total of 80 individual measurements" for each analyte on each platform.
  • Method Correlation: Data from "dried blood spots enriched with the analytes of interest," specifically "5 levels times 5 runs per analyte" resulted in 25 means per platform for each analyte (80 individual measurements total, as above).
• Clinical Test Set:
  • Clinical Correlation (Percent Agreement): 2499 random newborn screening specimens (presumptive negative data set) and 17 specimens with true positive diagnoses. Some analytes specify 2598 total observations (2499 + 80 individual measurements from enriched samples for other tests?), while others specify 2518* (2499 presumptive negatives + 19 true positives, including newly acquired NKH and H-ALA samples mentioned in footnote).
  • True Positive Samples: 17 samples with true positive diagnoses representing 14 disorders.
• Data Provenance: The document does not specify the country of origin for the samples. It mentions "newborn heel prick blood samples dried on filter paper," which is a standard collection method. The data is retrospective in the sense that these were pre-existing biological samples used for evaluation. It's not a prospective collection of new patients for this specific study.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications

This study focuses on diagnostic device performance (quantitative measurements of analytes) rather than interpretive tasks that would typically require human expert adjudication of images or complex clinical scenarios.

• Analytical Performance (Precision, Recovery, Measurable Ranges, Method Correlation): Ground truth is established by the known concentrations of analytes in the spiked/enriched samples, and the quantitative measurements determined by specialized laboratory equipment (Mass Spectrometers). No human experts are involved in establishing this type of ground truth.
• Clinical Correlation and True Positive Samples: The "ground truth" for the 17 true positive samples is referred to as "true positive diagnoses." The document does not specify how these diagnoses were established (e.g., whether by pathology, genetic testing, or clinical consensus) nor does it mention the number or qualifications of experts involved in these initial diagnoses.

4. Adjudication Method for the Test Set

Not applicable. This is an analytical/quantitative device performance study rather than an interpretive study requiring human adjudication. The "agreement" for clinical correlation refers to the concordance between the numerical results of the TQD platform and the predicate platforms against established clinical cutoffs, not human expert consensus on a diagnosis.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC comparative effectiveness study was not done. This study is evaluating the analytical performance and clinical correlation of a laboratory diagnostic assay, not a device that requires human interpretation of outputs.

6. If a Standalone Study (algorithm only without human-in-the-loop performance) was done

Yes, this is essentially a standalone (algorithm only) study. The "device" is a reagent kit used on an automated mass spectrometry system. The study compares the quantitative results generated by the TQD platform (with the NeoBase kit) directly to the predicate MS2 and QMicro platforms (also using the NeoBase kit) without a human-in-the-loop interpretation step being evaluated as part of the primary outcome for device clearance. The output is a numerical concentration.

7. The Type of Ground Truth Used

• Analytical Performance: Ground truth is based on known concentrations in control and enriched samples. These are prepared by spiking analytes into a matrix (dried blood spots) at specific, verifiable concentrations.
• Clinical Correlation and True Positive Samples:
  • For the 2499 random newborn screening specimens, the "ground truth" for clinical "agreement" is whether the analyte concentrations fall above or below their respective clinical cutoffs (as determined by the predicate device).
  • For the 17 true positive samples, the ground truth is established clinical diagnoses of metabolic disorders ("true positive diagnoses").

8. The Sample Size for the Training Set

The document describes evaluation of the device performance, not the training of an AI algorithm requiring a specific "training set." This device is a reagent kit for a mass spectrometry system, not an AI/ML software device in the typical sense. Therefore, there is no explicit "training set" in the context of an AI model.

Historically, the predicate devices (MS2 and QMicro) and their associated kits would have undergone extensive validation and optimization (which could be conceptually analogous to a training phase, but for analytical chemistry rather than AI). The current study is demonstrating the equivalence of the NeoBase kit on a new platform (TQD) to these previously validated systems.

9. How the Ground Truth for the Training Set was Established

As there is no distinct "training set" for an AI algorithm in this context, this question is not applicable. The methods used in developing and validating the NeoBase kit and its use on mass spectrometry platforms would involve many iterations of experiments to establish linearity, accuracy, precision, and other analytical specifications. This process relies on robust analytical chemistry principles and reference materials with known concentrations, rather than a "ground truth" established by human experts for AI training.

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The NeoBase Non-derivatized MSMS reagent kit is intended for the measurement and evaluation of amino acids, succinylacetone, free carnitine, and acylcarnitine concentrations from newborn heel prick blood samples dried on filter paper. Quantitative analysis of these analytes (Table 1) and their relationship with each other is intended to provide analyte concentration profiles that may aid in screening newborns for metabolic disorders.

The measurement of amino acids, succinylacetone, free carnitine, and acylcarnitines with the NeoBase assay involves extraction of dried blood spots from newborns with a solution containing stable-isotope labeled internal standards and analysis using a tandem mass spectrometry (MSMS) system. The response of each analyte relative to their corresponding stable-isotope labeled internal standard is proportional to analyte concentration.

The provided 510(k) summary describes the NeoBase Non-derivatized MSMS Kit, intended for newborn screening of metabolic disorders by measuring amino acids, succinylacetone, free carnitine, and acylcarnitine concentrations from dried blood spots. The device's performance was compared to a legally marketed predicate device, the NeoGram Amino Acids and Acylcarnitines Tandem Mass Spectrometry Kit (K031878).

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" as numerical thresholds for precision, recovery, or correlation that the device must meet. Instead, it presents the device's performance characteristics and compares them to those reported for the predicate device to demonstrate substantial equivalence. The implication is that performance comparable to the predicate device is considered acceptable.

2. Sample Size Used for the Test Set and Data Provenance

• Non-clinical (Precision, Recovery, Measurable Ranges): The document doesn't specify a distinct "test set" for these parameters in terms of a separate sample size. The data for these characteristics is generated through laboratory experiments likely using controlled samples (e.g., spiked samples, internal controls) rather than clinical patient samples. The provenance is implied to be laboratory-generated.
• Method Correlation:
  • Sample Size: 158 samples.
  • Data Provenance: Not explicitly stated, but samples were "prepared in duplicates" and assayed using both devices. Implied to be laboratory-controlled or clinical samples processed for comparison, but specific origin (e.g., country) is not mentioned. Given the context of newborn screening, they would likely be dried blood spots.
• Clinical Correlation Studies:
  • Sample Size:
    • 9416 random neonatal samples
    • 104 samples with true positive diagnoses
    • 320 artificially enriched dried blood spots
  • Data Provenance: From two different US newborn screening laboratories. The studies evaluated the NeoBase kit "in parallel to the predicate device (identical specimens were analyzed as paired samples by both methods)." This suggests a retrospective collection of these samples, as they are referred to as "random neonatal samples" and "samples with true positive diagnoses."
  • True Positive Samples (Specific breakdown): 108 total true positive samples were analyzed (104 from screening sites + 4 Tyrosinemia Type I samples analyzed by PerkinElmer R&D). The two samples that weren't detected by either assay were CPT-2 and VLCAD cases which had degraded due to storage.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

The document does not specify the number of experts or their qualifications used to establish the ground truth for the clinical correlation studies or the true positive samples.

For the true positive samples, the text refers to them as "samples with true positive diagnoses" and later lists "Disorder Full name" for each, implying that the diagnoses were established clinically through standard diagnostic procedures. However, the exact method of ground truth confirmation or number of experts involved is not detailed.

4. Adjudication Method for the Test Set

The document does not describe an adjudication method for the test set.

For the "Clinical Correlation Studies," it states that "Clinical correlation was established by assessing whether or not the methods were concordant in determining the paired samples to have analyte concentration values above or below their corresponding cutoffs." This implies a direct comparison of the readings from the NeoBase and predicate device against predetermined clinical cutoffs, rather than an expert adjudication process determining the ultimate "true" status of each sample for the purpose of the study.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done.

This device is an in vitro diagnostic (IVD) kit for quantitative measurement of analytes using tandem mass spectrometry. Its performance evaluation focuses on analytical characteristics (precision, recovery, measurable range) and method correlation with a predicate device, as well as clinical correlation of quantitative measurements to established cutoffs. MRMC studies are typically used for imaging devices or other diagnostic tools where human readers interpret results, and the study would then compare human performance with and without AI assistance. This is not applicable here.

6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) Was Done

Yes, a standalone performance evaluation was done.

The entire study described in the 510(k) refers to the performance of the device kit (NeoBase Non-derivatized MSMS Kit) itself. This is an assay system that produces quantitative values. The precision, recovery, measurable ranges, and direct comparisons of analyte concentrations to clinical cutoffs are all measures of the kit's standalone analytical performance. Human involvement is limited to operating the instrument and following the assay protocol, not to interpreting ambiguous results in a way that would alter the quantitative output.

7. The Type of Ground Truth Used

• Non-clinical (Precision, Recovery, Measurable Ranges): The ground truth for these studies would be based on known concentrations of analytes in controlled, laboratory-prepared samples (e.g., spiked samples, calibrators).
• Method Correlation: The "ground truth" here is the measurement from the predicate device. The study compares the new device's measurements against those from the established predicate device.
• Clinical Correlation Studies:
  • For the 9416 random neonatal samples, the ground truth was effectively the clinical cutoff values for each analyte. Samples were categorized as "above or below their corresponding cutoffs."
  • For the 104 (plus 4 Tyrosinemia Type I) "true positive samples," the ground truth was the established clinical diagnosis of specific metabolic disorders (e.g., 3-Methylcrotonyl-CoA Carboxylase Deficiency, Phenylketonuria, Tyrosinemia Type I). This implies outcomes data or a strong clinical consensus for the natural diagnosis itself.

8. The Sample Size for the Training Set

The document does not explicitly mention a "training set" for the NeoBase Non-derivatized MSMS Kit. This is an in vitro diagnostic assay, not a machine learning algorithm that typically undergoes a distinct training phase on a large dataset. The development of such a kit involves analytical validation studies to optimize reagents and protocols, which is different from "training" an algorithm.

9. How the Ground Truth for the Training Set Was Established

As no training set is explicitly described in the context of an algorithm or machine learning, this question is not applicable based on the provided text. The "ground truth" in the development of an IVD kit is established through standard analytical chemistry principles, reference methods, and clinical validation.

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