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37 results for “measurement uncertainty”
Tutorial "Uncertainty assessment for thermal diffusivity measurement by laser flash method"
<p>E-learning module about the assessment of uncertainty associated with thermal diffusivity measurement performed at high temperature by the laser flash method. Part of a tutorial series prepared in the framework of the Hi-TRACE project. </p>
Surface hourly measurement data of O3, NO2 and PM2.5 for "Large modeling uncertainty in projecting decadal surface ozone changes over urban and industrial regions of China"
<p>Surface hourly measurement data of O3, NO2 and PM2.5 during summer of 2017.</p> <p>In the .csv files, the first column contains the ID for each measurement site. "lon", "lat" are longitude and latitude, respectively.</p> <p>Date format is "YYYYMMDD_hour".</p>
Brewer #150 UV measurements and ancillary data needed for its uncertainty evaluation
<p>All files uploaded are needed to evaluate the uncertainty of the UV measurements recorded by the Brewer MKIII double monochromator (No. 150). The uncertainty analysis was carried out using the Monte Carlo technique, which was implemented in a separate R file (doi: 10.5281/zenodo.8046562). Files contain all the necessary information to characterize Brewer #150 (cosine correction, raw counts, lamp irradiance, responsivity instabilities, noise and wavelength shifts).</p>
Quantification of uncertainties introduced by data-processing procedures of sap flow measurements using the cut-tree method on a large mature tree
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Data from: Navigating “tip fog”: Embracing uncertainty in tip measurements
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Data from: Quantification and mitigation of uncertainties in thermal conductivity measurements using a modified ASTM D5470 thermal resistance tester
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Companion for "Measuring Phenology Uncertainty with Large Scale Image Processing"
<p>This is the software and dataset companion for the paper entitled "Measuring Phenology Uncertainty with Large Scale Image Processing". Further instructions can be found in the README.org file.</p>
Validation of an Uncertainty Propagation Method for Moving-Boat ADCP Discharge Measurements
<p>ADCP intercomparisons data from Génissiat (2010) and Chauvan (2016). Data used in the article <strong>Validation of an Uncertainty Propagation Method for Moving-Boat ADCP Discharge Measurements</strong>, <em>Water Resources Research</em>, Despax et al..</p>
Data in "The uncertainties in the laboratory-measured short-wave refractive indices of mineral dust aerosols and the derived optical properties: A theoretical assessment"
<p>This is the data for publication "The uncertainties in the laboratory-measured short-wave refractive indices of mineral dust aerosols and the derived optical properties: A theoretical assessment"</p> <p>Version 1: data</p> <p>Version 2: rename the data files and add a readme file</p>
UV scans measured by Brewer #150 during the XVI intercomparison campaign of the RBCC-E and their associated uncertainties
<p>All files uploaded are needed to evaluate the uncertainty of the UV measurements recorded by the Brewer MKIII double monochromator (No. 150). The 'data.rar' contains the UV scans measured by Brewer #150 during the XVI intercomparison campaign of the RBCC-E and their associated uncertainties and all the necessary information to characterize Brewer #150 (cosine correction, raw counts, lamp irradiance, responsivity instabilities, noise and wavelength shifts). The uncertainty analysis was carried out using two methodologies: the GUM uncertainty framework (based on the law of propagation of uncertainties) and the Monte Carlo technique. Both approaches are implemented in a separate R file (doi: https://doi.org/10.5281/zenodo.10973560).</p> <p>The previous version used the standard deviation instead of the standard deviation (as recommended by the GUM) for the analysis of the uncertainty of dark counts. This second version corrects this.</p>
Data for T-MTT X-parameter Measurement Uncertainty Paper
<p>Data in support of T-MTT paper.</p>
Data from: Not Normal: the uncertainties of scientific measurements
Judging the significance and reproducibility of quantitative research requires a good understanding of relevant uncertainties, but it is often unclear how well these have been evaluated and what they imply. Reported scientific uncertainties were studied by analysing 41 000 measurements of 3200 quantities from medicine, nuclear and particle physics, and interlaboratory comparisons ranging from chemistry to toxicology. Outliers are common, with 5σ disagreements up to five orders of magnitude more frequent than naively expected. Uncertainty-normalized differences between multiple measurements of the same quantity are consistent with heavy-tailed Student's t-distributions that are often almost Cauchy, far from a Gaussian Normal bell curve. Medical research uncertainties are generally as well evaluated as those in physics, but physics uncertainty improves more rapidly, making feasible simple significance criteria such as the 5σ discovery convention in particle physics. Contributions to measurement uncertainty from mistakes and unknown problems are not completely unpredictable. Such errors appear to have power-law distributions consistent with how designed complex systems fail, and how unknown systematic errors are constrained by researchers. This better understanding may help improve analysis and meta-analysis of data, and help scientists and the public have more realistic expectations of what scientific results imply.
Robust Active Measuring under Model Uncertainty - Code
<p>Repository containing code, as well as gathered data, as used for the paper</p> <blockquote> <p>Merlijn Krale, Thiago D. Simao, Jana Tumova, Nils Jansen<br>Robust Active Measuring under Model Uncertainty<br>In AAAI, 2024.</p> </blockquote> <p>For instructions, see the readme.md file in the repository.</p> <p>All code can also be found on GitHub, at <a href="https://github.com/LAVA-LAB/RATM">https://github.com/LAVA-LAB/RATM</a>.</p>
Dataset for publication "Uncertainty assessment for very high temperature thermal diffusivity measurements on molybdenum, tungsten and isotropic graphite"
<p>Experimental data presented in the paper:</p> <p>Hay B., Beaumont O., Failleau G., Fleurence N., Grelard M., Razouk R., Davée G., Hameury J., Uncertainty assessment for very high temperature thermal diffusivity measurements on molybdenum, tungsten and isotropic graphite, <em>International Journal of Thermophysics</em> 43:2 (2022). https://doi.org/10.1007/s10765-021-02926-6.</p> <p>Excel file contains the data for Figures 3 to 5.</p>
Digital representation of measurement uncertainty: a case study linking an RMO key comparison with a CIPM Key Comparison
<pre>This dataset is associated with a publication of the same name (currently submitted to the MDPI journal Metrology). It contains digital records (JSON files) of participant results as well as DoE results obtained from data processing. Python modules to display the contents of these files are provided as are modules for the comparison analyses. The GUM Tree Calculator (GTC) Python software package is required (version~1.3.6, or above: https://github.com/MSLNZ/GTC).</pre>
Data from: Not Normal: the uncertainties of scientific measurements
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Measurement of the Intolerance to Uncertainty in Osteopaths
ClinicalTrials.gov study NCT06695806. IPD Sharing: YES. Countries: 1. Publications: 0.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.