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47 results found

SRM 2969 Vitamin D Metabolites in Frozen Human Serum (Total 25-Hydroxyvitamin D Low Level) Data

Data provided by  National Institute of Standards and Technology

SRM 2969 Electronic files containing certified values and their uncertainties, and the data used to assign those values

Tags: vitamin D,25-hydroxyvitamin D,serum,mass spectrometry,

Modified: 2024-02-22

Views: 0

SRM 2970 Vitamin D Metabolites in Frozen Human Serum (25-Hydroxyvitamin D2 High Level) Data

Data provided by  National Institute of Standards and Technology

Electronic files containing certified values and their uncertainties, and the data used to assign those values.

Tags: vitamin D,25-hydroxyvitamin D,serum,mass spectrometry,

Modified: 2024-02-22

Views: 0

**SUPERSEDED** Software and Data for Modeling OFDM Communication Signals with Generative Adversarial Networks

Data provided by  National Institute of Standards and Technology

This software and data have been superseded. Please visit https://doi.org/10.18434/mds2-2532

Tags: generative adversarial network,machine learning,wireless communications,

Modified: 2024-02-22

Views: 0

Data Supporting "Seabird Tissue Archival and Monitoring Project (STAMP) Data from 1999-2010"

Data provided by  National Institute of Standards and Technology

Here we provide curated analytical chemistry data for eggs collected from 1999 to 2010 on a subset of species and analytes that were measured regularly and reasonably systematically. Included in this publication are 487 samples analyzed for 174 ubiquitous environmental contaminants such as (poly)brominated diphenyl ethers (BDEs), mercury, organochlorine pesticides (OCPs), and polychlorinated biphenyls (PCBs). Data were collated to form a dataset useful in chemometric and related analyses of the marine ecosystem in the north Pacific Ocean.

Tags: NIST Biorepository,eggs,tissues,BDEs,PBDEs,PCBs,Pesticides,mercury,trace elements,heavy metals,organic,inorganic,chemistry,stable isotopes,genetics,Environment and Climate,chemometric,machine learning,ML,seabird,bird,Pacific Ocean,

Modified: 2024-02-22

Views: 0

ANDiE: the Autonomous Neutron Diffraction Explorer.

Data provided by  National Institute of Standards and Technology

ANDiE the Autonomous Neutron Diffraction Explorer is a tool for autonomously discovering the magnetic transition temperature and transition dynamics of a material from neutron diffraction experiments. The Jupyter notebooks used to implement ANDiE can be found here: https://github.com/usnistgov/ANDiE-v1_0 The Jupyter notebooks contained therein are of ANDiE as implemented at the WAND2 instrument at the HB-2C beamline at the High-Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL).

Tags: Autonomous Experiments,neutron diffraction,machine learning,Active Learning,Artificial Intelligence,

Modified: 2024-02-22

Views: 0

Closed-loop Autonomous Materials Exploration and Optimization 1.0

Data provided by  National Institute of Standards and Technology

Code and demonstration data for the paper, "On-the-fly closed-loop materials discovery via Bayesian active learning," Kusne, A.G., Yu, H., Wu, C. et al. Nat Commun 11, 5966 (2020). https://doi.org/10.1038/s41467-020 19597-w Code: Closed-loop autonomous materials exploration and optimization. This code is used to control an autonomous materials exploration and optimization platform. It guides subsequent experiments to learn about a material's phase map and target functional properties in a unified framework.

Tags: autonomous,machine learning,phase map,materials optimization,

Modified: 2024-02-22

Views: 0

MAM Consortium Interlaboratory Study Raw Data

Data provided by  National Institute of Standards and Technology

These LC-MS and LC-MS/MS raw data were collected for purposes of an interlaboratory study evaluating the multi-attribute method (MAM). Tryptic digests of native NISTmAb (the "Reference" and the "Unknown" samples), degraded NISTmAb (the "pH Stress" sample) and NISTmAb spiked with 15 heavy-labeled synthetic peptides (the "Spike" sample) were sent to each participating laboratory. One injection of each digest was acquired in MS-only mode, while a second injection was acquired in MS/MS mode.

Tags: attribute analytics,interlaboratory study,multi-attribute method,MAM Consortium,mass spectrometry,new peak detection,NPD,purity testing,round robin,targeted analytics,NISTmAb,

Modified: 2024-02-22

Views: 0

ml_uncertainty: A Python module for estimating uncertainty in predictions of machine learning models

Data provided by  National Institute of Standards and Technology

This software is a Python module for estimating uncertainty in predictions of machine learning models. It is a Python package that calculates uncertainties in machine learning models using bootstrapping and residual bootstrapping. It is intended to interface with scikit-learn but any Python package that uses a similar interface should work.

Tags: uncertainty analysis,machine learning,model calibration,

Modified: 2024-02-22

Views: 0

Construction of a Dual-enzyme, Subzero (-30 degree C) Chromatography System and Multi-channel Precision Temperature Controller for Hydrogen-Deuterium Exchange Mass Spectrometry

Data provided by  National Institute of Standards and Technology

This tutorial provides mechanical drawings, electrical schematics, parts lists, STL files for 3D-printed parts, IGS files, and instructions for automated machining necessary for construction of a dual-protease, subzero, liquid chromatography system for hydrogen-deuterium exchange mass spectrometry. Electrical schematics for construction of a multi-zone temperature controller that regulate to ±0.1 oC are also included in this tutorial.

Tags: liquid chromatography,hydrogen-deuterium exchange,mass spectrometry,precision,peptide,protein,proteolysis,proteomics,reference material,temperature control.,

Modified: 2024-02-22

Views: 0

Challenge Round 0 (Dry Run) Test Dataset

Data provided by  National Institute of Standards and Technology

This dataset was an initial test harness infrastructure test for the TrojAI program. It should not be used for research. Please use the more refined datasets generated for the other rounds. The data being generated and disseminated is training, validation, and test data used to construct 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.).

Tags: Trojan Detection,Artificial Intelligence,ai,machine learning,Adversarial Machine Learning,

Modified: 2024-02-22

Views: 0