SRM 3287 Blueberry (Fruit). This Standard Reference Material (SRM) is intended primarily for use in validating analytical methods for the determination of organic acids and nutrients in blueberries and similar materials. This SRM can also be used for quality assurance when assigning values to in-house control materials. A unit of SRM 3287 consists of five packets, each containing approximately 5 g of freeze-dried, powdered fruit. This data is public in the Certificate of Analysis for this material.

SRM 3290 Dry Cat Food - This Standard Reference Material (SRM) is intended primarily for use in validating methods for determining proximates, fatty acids, vitamins, elements, and amino acids in dry cat food and similar matrices. This SRM can also be used for quality assurance when assigning values to in-house control materials. This SRM is a blend of commercially available dry cat foods. A unit of SRM 3290 consists of five heat-sealed, aluminized pouches, each containing approximately 10 g of material. This data is public in the Certificate of Analysis for this material.

SRM 3532 Calcium-Containing Solid Oral Dosage Form - This Standard Reference Material (SRM) is intended primarily for validation of methods for determining cholecalciferol (vitamin D3) and elements in a calcium dietary supplement and similar materials. This SRM can also be used for quality assurance when assigning values to in-house reference materials. A unit of SRM 3532 consists of five packets, each containing approximately 10 g of material. This data is public in the Certificate of Analysis for this material.

This Standard Reference Material (SRM) is intended for use as an analytical standard of known potassium (K) and chloride (Cl-) content. This lot of potassium chloride (KCl) was prepared to ensure a material of high purity and homogeneity and has been assayed after drying at 500 °C. A unit of SRM 999c consists of a single glass bottle containing 30 g of the material. This data is public in the Certificate of Analysis for this material.

A comparison of the expanded uncertainty for certified values of iodine in food matrix CRMs. The CRMS were found by searching The European Virtual Institute for Speciation Analysis (EVISA) database using the terms "Iodine" and "Certified" in the Material category. The uncertainties are expanded uncertainties at approximately 95% confidence.

The Micronutrients Measurement Quality Assurance Program (MMQAP) was coordinated by the Chemical Sciences Division and supported measurement technology for selected fat- and water-soluble vitamins and carotenoids in human serum. This program was initiated in 1984 by the National Cancer Institute Division of Cancer Prevention and Control to ensure the long-term reliability of the measurements made while studying the possible cancer chemoprevention roles of these compounds.

Round 3 Training DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Round 2 Test DatasetThe data being generated and disseminated is the test data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform a variety of tasks (image classification, natural language processing, etc.). A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Round 2 Holdout DatasetThe data being generated and disseminated is the holdout data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform a variety of tasks (image classification, natural language processing, etc.). A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Round 3 Test DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.