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648 results for “uncertainties”

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zenodo32/100

A non-intrusive nuclear data uncertainty propagation study for the ARC fusion reactor design

<p>Dataset of perturbed nuclear data files employed in the Serpent Monte Carlo code for the nuclear data uncertainty propagation analysis of the Affordable, Robust and Compact (ARC) fusion reactor.&nbsp;</p>

opencc-by-4.0Nov 2022View details →
zenodo32/100

Architecture-based Uncertainty Impact Analysis to ensure Confidentiality - Data Set

<p>Data set of the Paper &quot;Architecture-based Uncertainty Impact Analysis to ensure Confidentiality&quot;.&nbsp;For more information, please see the README.md.</p>

opencc-by-4.0Jan 2023View details →
zenodo32/100

TRENDYv10 DGVM output for: Process-oriented analysis of dominant sources of uncertainty in the land carbon sink

<p><strong>New datasets saved as NCDF files.</strong></p> <p><strong>Data</strong></p> <p>Post-processed TRENDYv10 DGVM data covering the period 1901-2020. Each file contains monthly/annual mean values for 19 models: CABLE-POP, CLASSIC, CLASSIC-N, CLM5.0, DLEM, IBIS, ISAM, ISBA-CTRIP, JSBACH, JULES-ES-1.1, LPJ-GUESS, LPJ, LPX-Bern, OCN, ORCHIDEE, ORCHIDEEv3, SDGVM, VISIT, YIBs. See https://blogs.exeter.ac.uk/trendy/</p> <p>List of variables can be found at https://blogs.exeter.ac.uk/trendy/documents/ . File name: &#39;trendy_listofvariables_GCP2021&#39;.</p> <p>Data for three experiments (S1 - S3) is provided. For experiment details, see &#39;GlobalCarbonBudget-Protocol-2021-web&#39; at https://blogs.exeter.ac.uk/trendy/documents/</p> <p><strong>Code</strong></p> <p>All data processing code is also provided. Files starting &quot;raw#...&quot; are run in order 1-4. Then the figure/manuscript files are executed, starting with &quot;proc1..&quot; - &quot;proc3..&quot;. The remaining Figure scripts (Figures 1-5 and S1-S8) and &quot;temp_changes.R&quot; can be run in any order.</p> <p>Any enquiries, contact Mike O&#39;Sullivan at m.osullivan@exeter.ac.uk</p>

opencc-by-4.0Jul 2022View details →
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Analysis and Data of "Adaptive tuning of human learning and choice variability to unexpected uncertainty"

<p>Data and analysis scripts&nbsp;in &quot;Adaptive tuning of human learning and choice variability to unexpected uncertainty&quot;. See&nbsp;https://github.com/jlexternal/RLVOLUNP_ana for directory structure.&nbsp;</p>

opencc-by-4.0Jan 2023View details →
zenodo32/100

Supplementary material 4 from: Auliya M, Altherr S, Nithart C, Hughes A, Bickford D (2023) Numerous uncertainties in the multifaceted global trade in frogs' legs with the EU as the major consumer. Nature Conservation 51: 71-135. https://doi.org/10.3897/natureconservation.51.93868

Amphibian species assessed in the IUCN Red List that are utilized either doemticalyy/nationally and or internationally

opencc-zeroFeb 2023View details →
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Supplementary material 2 from: Auliya M, Altherr S, Nithart C, Hughes A, Bickford D (2023) Numerous uncertainties in the multifaceted global trade in frogs' legs with the EU as the major consumer. Nature Conservation 51: 71-135. https://doi.org/10.3897/natureconservation.51.93868

Anuran species assessed in the IUCN Red List with uncertainties mainly prevailing in national/international trade routes, and level of exploitation

opencc-zeroFeb 2023View details →
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FIG. 2 in Clearing up the Crystal Ball: Understanding Uncertainty in Future Climate Suitability Projections for Amphibians

FIG. 2.—Mean predicted change in suitable climate for amphibian species by citation and model parameters from the meta-analysis. Points represent means and bars represent 95% confidence intervals. Mean predicted change in suitable climate was calculated for each amphibian order within each study for each of the model settings, including Representative Concentration Pathway, Year, and Dispersal Limitation. Triangles indicate estimates from the case study, and circles indicate all other studies. A color version of this figure is available online.

opennotspecifiedJun 2020View details →
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FIG. 1 in Clearing up the Crystal Ball: Understanding Uncertainty in Future Climate Suitability Projections for Amphibians

FIG. 1.—Map of countries for which suitable climate has been projected under future climate scenarios for at least one amphibian species. Colors represent the number of studies in which a given country was included. A color version of this figure is available online.

opennotspecifiedJun 2020View details →
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FIG. 3 in Clearing up the Crystal Ball: Understanding Uncertainty in Future Climate Suitability Projections for Amphibians

FIG. 3.—Percent change in climate suitability predicted for each species in the case study. For each species, predicted percent change in climate suitability is shown for the year 2050 under 13 general circulation models and two representative concentration pathways (2.6, 8.5) climate scenarios for both the default Maxent species distribution models (SDMs; regularization multiplier ¼ 1; open red boxes) and the best-fit SDM (Akaike information criterion; ΔAICc ¼ 0; shaded blue boxes) for three levels of dispersal: no dispersal, limited, or unlimited. Boxplots show median, interquartile range, and minimum and maximum values. A color version of this figure is available online.

opennotspecifiedJun 2020View details →
zenodo32/100

Dataset for: Contribution to Uncertainty Propagation Associated with On-Site Calibration of Infrasound Monitoring Systems

<p>Dataset containing the response data for the calibration of the MB5 microbarometer (Figure 5), the&nbsp;WNRS (Figure 6) and the sensor (Figure 8).</p>

opencc-by-4.0Mar 2023View details →
zenodo32/100

Supporting data for ''Sea surface warming patterns drive hydrological sensitivity uncertainties"

<p>Supporting data for our work on Nature Climate Change. You will find:</p> <p>&nbsp;- Integrated desired fireds from the CAM5 patch experiments,</p> <p>&nbsp;- Post-processed data from CMIP5 and CMIP6 models,</p> <p>&nbsp;- python codes for generating the plots in the manuscript.</p>

opencc-by-4.0Mar 2023View details →
zenodo32/100

Data Archive for "Latent diffusion models for generative precipitation nowcasting with accurate uncertainty quantification"

<p>This repository contains the training data and pretrained models for the paper &quot;Latent diffusion models for generative precipitation nowcasting with accurate uncertainty quantification&quot;.</p> <p>To use the data, clone the repository at <a href="https://github.com/MeteoSwiss/ldcast">https://github.com/MeteoSwiss/ldcast</a>. Unzip the files as follows:</p> <ul> <li>Demo files &quot;ldcast-demo-20210622.zip&quot; to the &quot;data&quot; directory</li> <li>Training and evaluation data archive &quot;ldcast-datasets.zip&quot; to the &quot;data&quot; directory</li> <li>Pretrained model archive &quot;models-genforecast.zip&quot; to the &quot;models&quot; directory</li> </ul>

opencc-by-nc-sa-4.0Mar 2023View details →
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Supplemental data for "Uncertainty in Land Use Obscures Global Soil Organic Carbon Stock Estimates"

<p>These are supporting data for the manuscript: &quot;Uncertainty in Land Use Obscures Global Soil Organic Carbon Stock Estimates.&quot; They include data for the figures showing the spatial dynamics of cropland and LULCC-induced SOC loss etc,&nbsp;including Fig.3, Fig.6, Fig.9, and Fig.10.</p>

opencc-by-4.0Apr 2023View details →
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Data for paper "Low Uncertainty Thermodynamic Temperature Above the Silver Point Using Relative Primary Radiometry" submitted to ITS10: International Temperature Symposium, Anaheim 2023

<p>Data and evaluation used to set up a thermodynamic temperature scale in line with the mise-en-pratique for&nbsp;the definition of the kelvin and associated uncertainty budget.</p> <p>Used to assign temperatures to fixed points as part of&nbsp;18SIB02 &ldquo;Realising the redefined kelvin&rdquo;&nbsp;</p> <p>Presented at, and an open access paper submitted to&nbsp;proceedings of, ITS10: International Temperature Symposium Anaheim USA 2023</p>

opencc-by-4.0May 2023View details →
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Fig. 3 in Validation and uncertainty estimation of analytical method for quantification of phytochelatins in aquatic plants by UPLC-MS

Fig. 3. Contribution of the sources (%) to the total uncertainty for the quantification of GSH and PCs in the L. gibba.

opennotspecifiedMar 2021View details →
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Fig. 1. a in Validation and uncertainty estimation of analytical method for quantification of phytochelatins in aquatic plants by UPLC-MS

Fig. 1. a) Total ion chromatogram (TIC) for the L. gibba sample, b) Extracted ion chromatogram of GSH and PCs from the TIC of L. gibba, c) Extracted ion chromatogram of GSH and PCs from the standard solution at 10 μg mL 1.

opennotspecifiedMar 2021View details →
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Fig. 2 in Validation and uncertainty estimation of analytical method for quantification of phytochelatins in aquatic plants by UPLC-MS

Fig. 2. Ishikawa diagram representing the main sources of uncertainties for measuring GSH and PC concentration in aquatic plants.

opennotspecifiedMar 2021View details →
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FIGURE 2 in Larval features of the Italian endemic Pyrochroa serraticornis kiesenwetteri Fairmaire, 1849 (Coleoptera: Pyrochroidae: Pyrochroinae) solve taxonomic uncertainties

FIGURE 2. Particularly sclerotized sagittal septum in the urogomphal pit of Pyrochroa serraticornis: A— urogomphal plate, dorsal view; B—urogomphal plate, posterior view. Scale bars = 0.5 mm.

opennotspecifiedAug 2023View details →
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FIGURE 1 in Larval features of the Italian endemic Pyrochroa serraticornis kiesenwetteri Fairmaire, 1849 (Coleoptera: Pyrochroidae: Pyrochroinae) solve taxonomic uncertainties

FIGURE 1. Larva of Pyrochroa serraticornis kiesenwetteri: A—habitus of pre-mature instar larva, dorsal view; B—last five abdominal urites with urogomphal plate, ventral view; C—urogomphal plate, posterior view: D— mandibles: ventral view (upper side), inner view (lower side), left mandible (right side), right mandible (left side). Scale bars: A = 5 mm; B = 2 mm; C = 1 mm; D = 0.25 mm

opennotspecifiedAug 2023View details →
zenodo32/100

Estimation of the Uncertainties Introduced in Thermal Map Mosaic: A Case of Study with PIX4D Mapper Software

<p>Available data sets, used to analyse problems related to thermal mapping obtained from thermal data acquired from unmanned aerial systems (UAS) equipped with thermal cameras. We focused on an accurate analysis of uncertainties introduced by the PIX4D Mapper software.</p>

opencc-by-4.0Sep 2023View details →

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record