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641 results for “data validation”
Data from: Development and validation of a RAD-Seq target-capture based genotyping assay for routine application in advanced black tiger shrimp (Penaeus monodon) breeding programs
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Data from: cross-validation matters in species distribution models: a case study with goatfish species
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Data from: Validating marine Devonian biogeography: a study in bioregionalization
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Data reported in development and cross-validation of a veterans mental health risk factor screen
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Data from: Validation of serum neurofilaments as prognostic & potential pharmacodynamic biomarkers for ALS
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Data from: Field validation of an eDNA assay for nutria illuminates a role in invasive species management
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Data for: Validation of a nutria (Myocastor coypus) environmental DNA assay highlights considerations for sampling methodology
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Data from: Development of a sustainability assessment algorithm and its validation using case studies on cryogenic machining
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Data from: How to validate a Bayesian evolutionary model
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Data from: Validation of Quality-of-Life assessment tool for Ethiopian old age people
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Data from: Validation of a murine proteome-wide phage display library for identification of autoantibody specificities
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FIGURE 22 in Description of Pallisentis thapari n. sp. and a re-description of Acanthosentis seenghalae (Acanthocephala, Quadrigyridae, Pallisentinae) using morphological and molecular data, with analysis on the validity of the sub-genera of Pallisentis
FIGURE 22. Phylogenetic tree generated by Chaudhary et al. (2019) using maximum likelihood (ML) analysis of 18s rDNA sequence data of Pallisentis indica and related species. Tree modified from Chaudhary et al. (2019) to remove distance values and different branch lengths but retaining hypothesized phylogenetic relationships and to include the names of species associated with the sequences identified in the present work. Putative sub-genera (sensu Amin et al. 2000) indicated in color.
FIGURES 9–14 in Description of Pallisentis thapari n. sp. and a re-description of Acanthosentis seenghalae (Acanthocephala, Quadrigyridae, Pallisentinae) using morphological and molecular data, with analysis on the validity of the sub-genera of Pallisentis
FIGURES 9–14. Drawing of specimens of Acanthosentis seenghalae Chowhan, Gupta, Khera, 1988: 9. Male worm; 10. Proboscis; 11. Hooks of the proboscis; 12. Female worm; 13. Posterior end and gonopore; 14. Eggs. Scale bars: 9 = 1 mm; 10 and 12 = 500 µm; 11 = 20 µm; 13 = 200 µm; 14 = 100 µm.
Raw data on Validation Study of the Revised Spirituality and Spiritual Care Rating Scale (SSCRS): A Cross-Sectional Survey in Poland
<p>Raw data on Validation Study of the Revised Spirituality and Spiritual Care Rating Scale (SSCRS): A Cross-Sectional Survey in Poland.</p>
Data from: Microplastic prevalence in 4 Oregon rivers along a rural to urban gradient applying a cost‐effective validation technique
<p>Microplastics are ubiquitous in our environment and are found in rivers, streams, oceans, and even tap water. Riverine microplastics are relatively understudied compared to those in marine ecosystems. In Oregon, we sampled eight sites along four freshwater rivers spanning rural to urban areas to quantify microplastics. Plankton tow samples from sites along the Columbia, Willamette, Deschutes, and Rogue Rivers were analyzed using traditional light microscopy for initial microplastic counts. Application of Nile Red dye to validate microplastics improved microplastic identification, particularly for particles (Wilcox Test; p-value=0.001). Nile Red-corrected microfiber abundance was correlated with human population within five kilometers of the sample site (R²=0.554), though no such relationship was observed between microparticles and population (R²=0.183). This study finds plastics present in all samples from all sites, despite the range from undeveloped, remote stretches of river in rural areas to metropolitan sites within Portland, demonstrating the pervasive presence of plastic pollution<span> </span><span><span>in freshwater environments.</span></span></p>
Training and Testing Data, Associated Code, and SCAM Validations Code and Data for ResNet in moist physics (ResCu)
<p>Data and codes for a deep convolutional residual neural network moist physics parameterization (ResCu).</p> <p>In this new version, the randomly selected training data samples and part of testing data samples (June, July and August) are provided. They are processed into a new data structure, which can be directly utilized in training and testing. For the entire second year training samples and the entire third year testing samples, we provide them in a repository at Dryad (<a href="https://doi.org/10.6075/J0CZ35PP">https://doi.org/10.6075/J0CZ35PP</a> and https://doi.org/10.6075/J03J3BGF).</p> <p>Please download and decompress ResCu_Han_et_al_JAMES.tar.gz.</p> <p>Follow the instructions in README.txt and download the training and testing data (The Dryad depositary is provided in the description). </p> <p>Here we provide 3 parts of data and codes:</p> <p>1, Training and testing data from SPCAM;</p> <p>2, Training and testing codes for ResCu and many other NN architectures;</p> <p>3, SCAM validations.</p> <p> </p>
Storm-Time Plasma Pressure Inferred from Multi-Mission Measurements and Its Validation using Van Allen Probes Particle Data
<p>Data associated with Space Weather Journal manuscript submission titled: "Storm-Time Plasma Pressure Inferred from Multi-Mission Measurements and Its Validation using Van Allen Probes Particle Data". This includes all the digital data that was used in constructing the Figures from the main text, along with files containing the fit set of coefficients and parameters for the model, and files describing the subset of magnetometer used for fitting the model. </p>
Supporting Information for "How long is too long? Variogram analysis of AERONET data to aid aerosol validation and intercomparison studies"
<p>This contains data sets and their description for the paper "How long is too long? Variogram analysis of AERONET data to aid aerosol validation and intercomparison studies" submitted to the journal Earth and Space Science by this author. This study investigates the uncertainty introduced into comparisons (between e.g. AERONET ground observations, satellite retrievals, or model simulations) of aerosol optical properties due to differences in time of observation between the data sets. This uncertainty source has historically been neglected but is potentially important in some situations.</p> <p> </p> <p>Journal policies are that Supporting Information data sets can no longer be archived with the paper, but instead should be uploaded to a separate repository. As a result, I have uploaded these data here.</p> <p> </p> <p>This data set consists of one pdf file describing the data sets, and then two zip archives containing the data (ASCII format). The total size is approximately 10 MB. These data files allow the reproduction of analysis results in this paper, and enable researchers to estimate temporal mismatch uncertainties in their own analyses involving AERONET sites.</p>
Data from: Standardization and validation of a panel of cross-species microsatellites to individually identify the Asiatic wild dog (Cuon alpinus)
The Asiatic wild dog or dhole (Cuon alpinus) is a highly elusive, monophyletic, forest dwelling, social canid distributed across south and Southeast Asia. Severe pressures from habitat loss, prey depletion, disease, human persecution and interspecific competition resulted in global population decline in dholes. Despite a declining population trend, detailed information on population size, ecology, demography and genetics is lacking. Generating reliable information at landscape level for dholes is challenging due to their secretive behaviour and monomorphic physical features. Recent advances in non-invasive DNA-based tools can be used to monitor populations and individuals across large landscapes. In this paper, we describe standardization and validation of faecal DNA-based methods for individual identification of dholes. We tested this method on 249 field-collected dhole faeces from five protected areas of the central Indian landscape in the state of Maharashtra, India. Results We tested a total of 18 cross-species markers and developed a panel of 12 markers for unambiguous individual identification of dholes. This marker panel identified 101 unique individuals from faecal samples collected across our pilot field study area. These loci showed varied level of amplification success (57-88%), polymorphism (3-9 alleles), heterozygosity (0.23-0.63) and produced a cumulative misidentification rate or PID(unbiased) and PID(sibs) value of 4.7x10-10 and 1.5x10-4, respectively, indicating a high statistical power in individual discrimination from poor quality samples. Conclusion Our results demonstrated that the selected panel of 12 microsatellite loci can conclusively identify dholes from poor quality, non-invasive biological samples and help in exploring various population parameters. This genetic approach would be useful in dhole population estimation across its range and will help in assessing population trends and other genetic parameters for this elusive, social carnivore.
Input and validation data for the Askervein Hill benchmark
<p>This dataset has been generated within the IEA-Wind Task 31 Wakebench project to validate microscale flow models over complex terrain. The data has been digitized from the original technical reports of the experiment from Taylor and Teunissen (1983/1985).</p>
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.