Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
237
datasets available to search
ShareScore release 0.7.1
Dataset results
237 results for “Sensitivity Analysis”
Drainage reorganisation and species evolution: model sensitivity analysis data
<p>Data description:</p> <ul> <li><strong>‘trial_factor_values.csv’:</strong> The factor values for experiment trials were generated using a quasi-random Sobol sequence (Sobol, 1967). The table field, ‘initial_landscape_id’ is the identifier for unique combinations of the following factor values that controlled the landscape elevation in the initial conditions phase of the model: initial elevation seed, <span class="math-tex">\(U\)</span>, <span class="math-tex">\(K\)</span>, and <span class="math-tex">\(k_d\)</span>. The factors, <span class="math-tex">\(U\)</span>, <span class="math-tex">\(K\)</span>, <span class="math-tex">\(k_d\)</span>, <span class="math-tex">\(P_m\)</span>, and allopatric wait time varied logarithmically. The values of these factors in the file are the exponent of base 10.</li> <li><strong>‘trial_response_values_initial_conditions_phase.csv’:</strong> Topographic relief at steady state along with the model time to initial steady state are the trial model responses included in the file. Values are listed for each initial landscape ID rather than trial because many trials had the same combinations of the factors that controlled the topography of the initial landscape. </li> <li><strong>‘trial_response_values_perturb_phase_base_level_fall_scenario.csv’ and ‘trial_response_values_perturb_phase_fault_throw_scenario.csv’:</strong> Model responses of the perturb phase for base level fall and fault throw scenario along with the initial landscape ID, species count values, and the model time back to steady state.</li> <li><strong>The files beginning with `sobol`</strong>: the sensitivity analysis results output by the software, ‘SALib’ (Herman and Usher, 2017). ‘S1’, ‘S2’, and ‘ST’ in the file name indicates if the file contains data of the Sobol first, second, or total order effect, respectively.</li> </ul>
Dataset of "Sensitivity analysis in photodynamics: How the electronic structure controls cis-stilbene photodynamics?"
<p>The techniques of computational photodynamics are increasingly employed to unravel reaction mechanisms and interpret experiments. However, inaccuracies in nonadiabatic dynamics can lead to misinterpretations, particularly when calculated observables exhibit low sensitivity to the underlying dynamics. This issue is exemplified in the photochemistry of cis-stilbene, where similar experimental outcomes have been differently interpreted based on the electronic structures supporting nonadiabatic dynamics. This study examines the predictions of cis-stilbene photochemistry using trajectory surface hopping methods coupled with various electronic structures (OM3-MRCISD, SA2-CASSCF, XMS-SA2-CASPT2, and XMS-SA3-CASPT2) and assesses their ability to interpret experimental observations. Although the excited-state lifetimes show consistency, ranging from 360 fs to 295 fs, the reaction quantum yields vary significantly. The quantum yield for cyclization ranges from nearly zero to 35% while the photoisomerization channel can either exceed 50% or be entirely suppressed completely in the second case. Intriguingly, the calculated photoelectron signal is not strikingly different for different reaction scenarios, making the methods seemingly reliable when treated separately Furthermore, analyzing stationary points on the potential energy surface does not reliably predict simulation outcomes, nor does it aid in selecting a specific method before simulations. Therefore, we advocate for incorporating sensitivity analyses in the simulation protocol. While employing an ensemble of methods is impractical, nonadiabatic simulations with external bias present a resource-efficient approach to achieve this goal.</p>
Dataset for paper "Ejecta cloud distributions for the statistical analysis of impact cratering events onto asteroids' surfaces: a sensitivity analysis"
<p>Dataset for the paper "Ejecta cloud distributions for the statistical analysis of impact cratering events onto asteroids' surfaces: a sensitivity analysis" published in Icarus.</p>
Statistical analysis and dataset for: A high-throughput and sensitive method for food preference assays in walking insects
<p>Linked to the journal article published in bioRxiv (https://doi.org/10.1101/2024.04.10.588882).</p> <p><em><strong>Abstract</strong></em></p> <p>Insects pose significant challenges in both pest management and ecological conservation. Often, the most effective strategy is employing toxicant-laced baits, which must also be designed to specifically attract and be preferred by the targeted species for optimal species-specific effectiveness. However, traditional methods for measuring bait preference are either non-comparative, meaning that most animals only ever taste one bait, or suffer from methodological or conceptual limitations. Here we demonstrate the value of direct comparison food preference assays using the invasive and pest ant <em>Linepithema humile </em>as a model. We compare the food preference sensitivity of non-comparative (one visit to a food source) and sequential comparative (visiting one type of food then another) assays at detecting low levels of aversive quinine in sucrose solution. We then introduce and test a novel dual-choice feeder method for simultaneous comparative evaluation of bait preferences, testing its effectiveness in discerning between foods with varying quinine or sucrose levels. While the non-sequential assay could not detect aversion to 1.25mM quinine in 1M sucrose, the sequential comparative approach detected aversion to quinine levels as low as 0.94mM. The novel dual feeder method approach could detect aversion to quinine levels as low as 0.31mM, and also preference for 1M sucrose over 0.75M sucrose. The dual-feeder method, combines the sensitivity of comparative evaluation with high throughput, ease of use, and avoidance of interpretational issues. This innovative approach offers a promising tool for rapid and effective testing of bait solutions, contributing to the development of targeted control strategies. Moreover, the method can be easily modified for application to a wide range of walking insects, such as cockroaches, crickets, and beetles.</p>
Predictability Limit of the 2021 Pacific Northwest Heatwave from Deep-Learning Sensitivity Analysis
<p>The attached two datasets are the optimized inputs used to analyze predictability limits in the paper Predictability Limit of the 2021 Pacific Northwest Heatwave from Deep-Learning Sensitivity Analysis. Specifically, the datasets correspond to the inputs used to produce the blue (global) and green (regional) loss curves in Figure S2. They are NetCDF files of dimensions batch (1), time (2), latitude (181), longitude (360), pressure levels (13), and may be run as Graphcast model inputs to initiate a forecast at 00 UTC 20 June 2021. Both datasets have been systematically perturbed to reduce the Graphcast model's loss function, which minimizes forecast eror as described in the manuscript. The global input seeks to reduce the loss over the entire globe, while the regional input seeks only to minimize error within the Pacific Northwest (42N to 60N and 130W to 110W). The optimized inputs result in a reduction of the loss by approximately 85% (global) and 93% (regional) when compared to a control Graphcast forecast without perturbations.</p>
MITgcm Dataset for paper: Sensitivity analysis of a data-driven model of ocean temperature
<p>MITgcm dataset used in paper, Sensitivity analysis of a data-driven model of ocean temperature, made available here. The dataset comes from running a sector config of the MITgcm model, briefly described in the paper. This dataset is used to train the regression model described in the paper.</p> <p>Updated to include ncra_cat_tave.nc file which was accidentally missed on first version.</p>
Intraspecific variation in the sensitivity of bees to pesticides: a comparative analysis in Bombus terrestris and Osmia bicornis
<p>These files describe the archived CSV files associated with the publication "Intra-specific variation in sensitivity of Bombus terrestris and Osmia bicornis to three pesticides"</p> <p>By Alberto Linguadoca, Margret Jürison, Sara Hellström, Edward A. Straw1, Peter Šima, Reet Karise, Cecilia Costa, Giorgia Serra, Roberto Colombo, Robert J. Paxton, Marika Mänd, Mark J. F. Brown<br> </p>
Dataset for "Low-cloud feedback in CAM5-CLUBB: physical mechanisms and parameter sensitivity analysis"
<p>This repository contains the data of 512 perturbed-parameter ensemble experiments and CAM5-CLUBB default experiments for the paper "Low-cloud feedback in CAM5-CLUBB: physical mechanisms and parameter sensitivity analysis".</p> <p>In this paper, the quasi-Monte Carlo (QMC) sampling approach is applied to explore the high-dimensional space. 512 samples are generated with the 18 perturbed parameters. For each parameter sample, a pair of experiments is performed: the control one is based on the climatological sea surface temperature (SST), and the 4K experiment applies a uniform +4K SST perturbation to the control experiment. The total of 1024 simulations are then performed. In addition, CAM5-CLUBB default experiments that adopt the default values of the 18 selected parameters as in Bogenschutz et al. (2013) are performed to provide detailed model diagnostics for analyzing physical mechanisms of the cloud feedback, and they include both control and +4K simulations. Each simulation is run for 5 years and 4 months, forced by climatological SSTs. Monthly mean results from the last 5 years are analysed in this study.</p> <p>Note: data uploaded here is annual-mean and the dimension name 'time' in the files (CAM5-CLUBB_PPE_512*.nc) is the number of 512 PPE member.</p>
Assessment of the Vulnerability of Permafrost Carbon to Climate Change: A Sensitivity Analysis among Models
This activity is a comparison of how large-scale models represent permafrost carbon dynamics into the future (2010-2299). Model responses were evaluated at several temporal scales. To the extent possible, we standardized driver data and simulation procedures among the models. However, the protocol has been set up so that each model can build upon the procedures used to produce the outputs for historical analysis (1960- 2009) that was published in McGuire et al. 2016 (Global Biogeochemical Cycles 30:1015-1037, doi:10.1002/2016GB005405). Note that this comparison is an offline model comparison in which we assessed the sensitivity of the responses of the models to somewhat standardized forcing data. The activity compared among the models: Carbon dynamics: Predictions of average annual C fluxes (GPP, NPP, RH, CH4 fluxes, disturbance-related emissions, dissolved organic carbon export, lateral land used fluxes, etc.) and major pools for the northern permafrost region for the 2010-2299 period. Soil thermal dynamics: Predictions of annual soil thermal and hydrological dynamics at prescribed depths and the maximum annual active layer depth (in permafrost locations) for the 2010-2299 time period. The spatial simulation data for this project are are available through the National Snow and Ice Data Center (doi: 10.5067/ZRL5WJKN01XM).
Global sensitivity analysis to enhance the transparency and rigour of energy system optimisation modelling - Supplementary Material
<p>Supplementary material for the manuscript "Global sensitivity analysis to enhance the transparency and rigour of energy system optimisation modelling".</p> <p>This deposit contains all data and visualization scripts needed to replicate results in the manuscript.This includes user created figures, model input files, model output files, configuration files for running the workflow, and all scripts needed to process results.</p> <p>In addition to the European Commission, we acknowledge that Trevor Barnes' contribution to this paper was funded via a Mitacs Globalink Research Award, grant number IT2569</p>
Data for sensitivity analysis
<p>To explore how the height of hydrofracture zone changes with parameter, use all the eight independent parameters, namely (1) Biot-Willis poro-elastic constant, (2), Poisson ratio of the strata, (3) bulk density of the rock, (4) tensile strength of the rock, (5) maximum overpressure in the deep-seated reservoir, (6) rock permeability, (7) permeability growth rate in the fracture, (8) bottom radius of the hydrofracture zone.</p><p>The sensitivity analysis simulated 90 scenarios using values of the above-mentioned parameters. Each independent variable in this dataset is populated with randomly generated numbers.</p>
Age estimation of captive Asian elephants (Elephas maximus) based on DNA methylation: An exploratory analysis using methylation-sensitive high-resolution melting (MS-HRM)
<p>Age is an important parameter for bettering the understanding of biodemographic trends-development, survival, reproduction and environmental effects-critical for conservation. However, current age estimation methods are challenging to apply to many species, and no standardised technique has been adopted yet. This study examined the potential use of methylation-sensitive high-resolution melting (MS-HRM), a labour, time, and cost-effective method to estimate chronological age from DNA methylation in Asian elephants (<em>Elephas maximus</em>). The objective of this study was to investigate the accuracy and validation of MS-HRM use for age determination in long-lived species, such as Asian elephants. The average lifespan of Asian elephants is between 50-70 years but some have been known to survive for more than 80 years. DNA was extracted from 53 blood samples of captive Asian elephants across 11 zoos in Japan, with known ages ranging from a few months to 65 years. Methylation rates of two candidate age-related epigenetic genes, <em>RALYL</em> and <em>TET2,</em> were significantly correlated with chronological age. Finally, we established a linear, unisex age estimation model with a mean absolute error (MAE) of 7.36 years. This exploratory study suggests an avenue to further explore MS-HRM as an alternative method to estimate the chronological age of Asian elephants.</p>
Data for sensitivity analysis of Hübler, M., M. Wiese, M. Braun and J. Damster (2023): The distributional effects of CO2 pricing at home and at the border on German income groups
<p>This dataset contains the output files used in the sensitivity analysis of the computable general equilibrium (CGE) model developed in Hübler et al. (2023). Each folder is labeled with the respective set of sector-level elasticity of substitution parameters considered in the analysis: elasticities between domestically produced versus imported goods (esubd), Armington elasticities (esubm) and elasticities between production factors (esubva).</p> <p>For each set of parameters, we generate 1000 random draws from a +-10 % interval around each of the sector-specific elasticities, resulting in 1000 sets of sectoral parameter values. Each .xlsx output file located in a dedicated subfolder corresponds to a model run with a specific set of parameter values. In addition, we conduct sensitivity analyses of two individual parameters, namely the CO2 target (CO2factor) considered in our policy scenarios and the elasticity of substitution in consumption (esub_cons).</p> <p>The sensitivity analysis is carried out using the <a href="https://snakemake.readthedocs.io/en/stable/">Snakeflow</a> workflow management system, and R code for generating parameter spaces and processing the output files is available on <a href="https://github.com/mariuslbraun/climate-trade-distribution-sensitivity">GitHub</a>.</p>
Sensitivity analysis script for: Why so many polyploids?
<p>While polyploids are common in nature, existing models suggest that polyploid establishment should be difficult and rare. We explore this apparent paradox by focusing on the role of unreduced gametes, as their union is the main route for formation of neopolyploids. Production of such gametes is affected by genetic and environmental factors, resulting in variation in the formation rate of unreduced gametes (<em>u</em>). Once formed, neopolyploids face minority cytotype exclusion (MCE) due to a lack of viable mating opportunities. More than a dozen theoretical models have explored factors that could permit neopolyploids to overcome minority cytotype exclusion and become established. Until now, however, none have explored variability in <em>u</em> and its consequences for the rate of polyploid establishment. Here, we determine the distribution that best fits available empirical data on <em>u</em>. We perform a global sensitivity analysis exploring the consequences of using empirical distributions of <em>u</em> to investigate effects on polyploid establishment. We determined in many cases <em>u</em> is best fit by a log-normal distribution. We found environmental stochasticity in <em>u</em> dramatically impacts model predictions when compared to a static <em>u</em>. Our results help reconcile previous modeling results suggesting high barriers to polyploid establishment with the observation that polyploids are common in nature.</p>
A Global Sensitivity Analysis of Parameter Uncertainty in the CLASSIC Model
<p>Input scripts, datasets and outputs used for the GSA methods. Please read the README and workflow files.</p>
Implementation and sensitivity analysis of a Dam-Reservoir OPeration model (DROP v1.0) over Spain - Supplement
<p>Supplement of the following scientific paper submitted in GMD :</p> <p><strong>Sadki M., Munier S., Boone A., Ricci S. : Implementation and sensitivity analysis of a Dam-Reservoir OPeration model (DROP v1.0) over Spain, Geoscientific Model Development, 2022. </strong></p> <p> </p>
Radio-frequency C-V measurements with subattofarad sensitivity: data and analysis script
<p>The attached files include:</p> <ul> <li>QCoDeS database containing all of the raw data underlying the results presented in the publication "Radio-frequency CV measurements with subattofarad sensitivity" by F.K. Malinowski at al. published in Physical Review Applied in 2022</li> <li>Jupyter Notebook file with Python scripts, that processes the raw data and outputs the figures embedded in the publication (except for the schematics of the devices and the rf circuitry).</li> </ul>
Sensitivity analysis of a mathematical model simulating the post-hepatectomy hemodynamics response
<p>Recently a lumped-parameter model of the cardiovascular system was proposed to simulate the hemodynamics response to partial hepatectomy and evaluate the risk of portal hypertension (PHT) due to this surgery. Model parameters are tuned based on each patient data. This work focuses on a global sensitivity analysis (SA) study of such model to better understand the main drivers of the clinical outputs of interest. The analysis suggests which parameters should be considered patient-specific and which can be assumed constant without losing in accuracy in the predictions. While performing the SA, model outputs need to be constrained to physiological ranges. An innovative approach exploits the features of the polynomial chaos expansion method to reduce the overall computational cost. The computed results give new insights on how to improve the calibration of some model parameters. Moreover the final parameter distributions enable the creation of a virtual population available for future works. Although this work is focused on partial hepatectomy, the pipeline can be applied to other cardiovascular hemodynamics models to gain insights for patient-specific parameterization and to define a physiologically relevant virtual population.</p>
KIEA-IRES Exploration II: Morris Sensitivity-analysis-driven Refinement
<p>This repository contains the data for the automated reaction network exploration of the Eschemoser-Claisen rearrangements of allyl alcohol and furfuryl alcohol using Morris sensitivity analysis as a measure for the targeted network refinement, as presented in</p> <p>Bensberg, M.; Reiher, M., Uncertainty-aware First-principles Exploration of Chemical Reaction Networks, **2023** arXiv, DOI: 10.48550/ARXIV.2312.15477.</p> <p> </p>
Fig. 3 in Repeatability Analysis Of Egg Shape In A Wild Tree Sparrow (Passer Montanus) Population: A Sensitive Method For Egg Shape Description
Fig. 3. The effect of egg-photographing on the description of outline. Panel a shows ten outlines described following the photos of ten randomly chosen eggs, panel b shows ten outlines described fol-
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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)
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.
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.