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109
datasets available to search
ShareScore release 0.9.0
Dataset results
109 results for “prediction accuracy”
Randomized Clinical Trial to Evaluate the Predictive Accuracy of a Gene Expression for Stage I-II Breast Cancer
ClinicalTrials.gov study NCT00336791. IPD Sharing: Not stated. Countries: 4. Publications: 1.
Improving Planned Surgical Case Duration Accuracy by Leveraging the EHR and Predictive Modeling
ClinicalTrials.gov study NCT03471377. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Accuracy of aCETIC Acid to Predict Histopathology of Colonic Polyps
ClinicalTrials.gov study NCT04157803. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Combining high-throughput phenotyping and genomic information to increase prediction and selection accuracy in wheat breeding
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Data from: Varying dataset resolution alters predictive accuracy of spatially explicit ensemble models for avian species distribution
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Data from: Prediction accuracies for growth and wood attributes of interior spruce in space using genotyping-by-sequencing
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Data from: Integrating soil properties into species distribution models enhances predictive accuracy for terricolous macrofungi
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Data from: Accuracy in the prediction of disease epidemics when ensembling simple but highly correlated models
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Data from: Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: prediction accuracy implications
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Validation of the predictive accuracy of health-state utility values based on the Lloyd model for metastatic or recurrent breast cancer in Japan
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Data from: Diagnostic accuracy of presepsin in predicting bacteremia in elderly patients admitted to the emergency department: prospective study in Japan
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Data from: Genomic prediction accuracies in space and time for height and wood density of Douglas-fir using exome capture as the genotyping platform
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Incorporation of soil-derived covariates in progeny testing and line selection to enhance genomic prediction accuracy in soybean breeding
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Data from: Modelled three-dimensional suction accuracy predicts prey capture success in three species of centrarchid fishes
Prey capture is critical for survival, and differences in correctly positioning and timing a strike (accuracy) are likely related to variation in capture success. However, an ability to quantify accuracy under natural conditions, particularly for fishes, is lacking. We developed a predictive model of suction hydrodynamics and applied it to natural behaviours using three-dimensional kinematics of three centrarchid fishes capturing evasive and non-evasive prey. A spheroid ingested volume of water (IVW) with dimensions predicted by peak gape and ram speed was verified with known hydrodynamics for two species. Differences in capture success occurred primarily with evasive prey (64–96% success). Micropterus salmoides had the greatest ram and gape when capturing evasive prey, resulting in the largest and most elongate IVW. Accuracy predicted capture success, although other factors may also be important. The lower accuracy previously observed in M. salmoides was not replicated, but this is likely due to more natural conditions in our study. Additionally, we discuss the role of modulation and integrated behaviours in shaping the IVW and determining accuracy. With our model, accuracy is a more accessible performance measure for suction-feeding fishes, which can be used to explore macroevolutionary patterns of prey capture evolution.
Data from: An upper bound for accuracy of prediction using GBLUP
This study aims at characterizing the asymptotic behavior of genomic prediction R2 as the size of the reference population increases for common or rare QTL alleles through simulations. Haplotypes derived from whole-genome sequence of 85 Caucasian individuals from the 1,000 Genomes Project were used to simulate random mating in a population of 10,000 individuals for at least 100 generations to create the LD structure in humans for a large number of individuals. To reduce computational demands, only SNPs within a 0.1M region of each of the first 5 chromosomes were used in simulations, and therefore, the total genome length simulated was 0.5M. When the genome length is 30M, to get the same genomic prediction R2 as with a 0.5M genome would require a reference population 60 fold larger. Three scenarios were considered varying in minor allele frequency distributions of markers and QTL, for h2 = 0.8 resembling height in humans. Total number of markers was 4,200 and QTL were 70 for each scenario. In this study, we considered the prediction accuracy in terms of an estimability problem, and thereby provided an upper bound for reliability of prediction, and thus, for prediction R2. Genomic prediction methods GBLUP, BayesB and BayesC were compared. Our results imply that for human height variable selection methods BayesB and BayesC applied to a 30M genome have no advantage over GBLUP when the size of reference population was small (<6,000 individuals), but are superior as more individuals are included in the reference population. All methods become asymptotically equivalent in terms of prediction R2, which approaches genomic heritability when the size of the reference population reaches 480,000 individuals.
The effect of different statistical methods on the accuracy of predicting genomic selection in beef cattle
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Supplementary material 1 from: Capinha C, Essl F, Seebens H, Pereira HM, Kühn I (2018) Models of alien species richness show moderate predictive accuracy and poor transferability. NeoBiota 38: 77-96. https://doi.org/10.3897/neobiota.38.23518
Table A1–A5 :
Closing in on Hydrologic Predictive Accuracy: Combining the Strengths of High-Fidelity and Physics-Agnostic Models
<p>The zip file contains a synthetic dataset that was used to construct the surrogate model.</p>
A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC Prediction
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Does a tradeoff between temporal stability and sampling frequency contribute to prediction accuracy of alternative stable states of soil moisture?
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ScienceDex guides
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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.