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726
datasets available to search
ShareScore release 0.9.0
Dataset results
726 results for “model evaluation”
Data from: Evaluating temporal and spatial transferability of a tidal inundation model for foraging waterbirds
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Data from: Evaluating migration hypotheses for the extinct Glyptotherium using Ecological Niche Modeling
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Evaluating the suitability of close-kin mark-recapture as a demographic modelling tool for a critically endangered elasmobranch population
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Model for evaluating seabirds preferences for hake offal in Patagonia
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RadCases evaluation results: Evaluating acute image ordering for real-world patient cases via language model alignment with radiological guidelines
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Data from: Integrating genomic data and simulations to evaluate alternative species distribution models and improve predictions of glacial refugia and future responses to climate change
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Isotope mixing scenarios and machine learning model in: To what extent are the source mixing models accurate: evaluation of the model accuracy and guidelines for the site-specific model selection
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Data from: Evaluating the effects of wolf culling on livestock predation when considering wolf population dynamics in an individual-based model
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Data from: Evaluating the importance of individual heterogeneity in reproduction to Weddell seal population dynamics using integral projection models
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Evaluation of large language model chatbot responses to psychotic prompts: numerical ratings of prompt-response pairs
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Feature Model for Scrum Adaptation - Evaluation Survey
<p>Feature Model for Scrum Adaptation - Evaluation Survey</p>
Scrum roles adaptations survey and feature model evaluation
<p>Scrum roles adaptations survey and feature model evaluation</p>
Interstate Transport of CO and BC and other relevant model evaluation data
<p>This zip file contains four sub-folders and 4 other files which are used in <strong>Bhardwaj et al., 2020</strong> submitted in <strong>JGR:Atmospheres</strong></p> <p><strong>1. bc_data</strong> : contains 15 files</p> <ul> <li>12 netcdf files (<strong>2014*_bc.nc</strong>) for each month having co-located WRF and observation data</li> <li>2 files (<strong>BC_seasonal_*.txt</strong>) which contains all BC surface observations over India from Kumar et al., (2015)</li> </ul> <p><strong>2. comp_MOPITT</strong> : contains 8 files</p> <ul> <li>4 netcdf files (<strong>wrf_mop_tc_co_*.nc</strong>; for four seasons defined in the paper) with WRF and MOPITT total CO column data</li> <li>4 netcdf files (<strong>wrf_mop_co_*.nc</strong>; for four seasons defined in the paper) with WRF and MOPITT CO profile data.</li> </ul> <p><strong>3. comp_TRMM</strong> contains 12 monthly netCDF files (<strong>comp_wrf_trmm_prec_2014*.nc</strong>) with WRF and TRMM data used in this study</p> <p><strong>4. NOAA_NCDC_ISD</strong> contains six netcdf files (<strong>wrf_obs_*.nc</strong>) for six regions (defined in this study) with co-located temperature and wind speed observations over India. The file also has WRF data for the same sites</p> <ul> <li>Two “<strong>wrfchemi_*z_d01</strong>” input emission files which are used for making emission flux (the above files) and mixing ratio plots (below files)</li> <li>Two files “<strong>state_contri_2014.nc</strong>” and “<strong>region_contri_2014.nc</strong>” have all information on interstate CO, BC for every six hours during 2014 from 30 states or six regions. These files are used for most plots in Bhardwaj et al., 2020.</li> </ul>
Data and code for training and evaluating machine learning models for thunderstorm prediction from reanalysis data
<p>FIXED Data and Python code for training and evaluating machine learning models for predicting thunderstorms, associated with the paper:</p> <p>"Evaluation of machine learning classifiers for predicting deep convection"</p> <p>by Peter Ukkonen and Antti Mäkelä (to appear in JAMES)</p> <p>The data (preprocessed inputs and outputs) is stored as netCDF files and .mat files which can be loaded with Python. </p>
An Empirical Evaluation about Using Models to Improve Preliminary Safety Analysis
<p>Video presentation of the paper "<em>An Empirical Evaluation about Using Models to Improve Preliminary Safety Analysis</em>" to appear at <strong>II Workshop de Modelagem e Simulação de sistemas intensivos em Software (II MSSiS) </strong>2020 co-located with CBSOFT 2020.</p> <p><strong>Abstract.</strong> <strong>Context</strong>: Safety analysis is an activity of fundamental importance in the development of safety-critical systems (SCS) to ensure that hazardous situations are properly found and mitigated. Such analysis is performed after a system requirements specification is available. Therefore, it is then worthwhile to investigate specification techniques to detect their strengths and weaknesses with respect to discovering hazards early in the development process. <strong>Objective</strong>: In this paper, we investigate similarities and differences in the results of a preliminary safety analysis from requirements specified using models in Business Process Modeling Notation (BPMN) and Textual Use Cases (TUC). <strong>Method</strong>: We adopted a controlled experiment as research method using computer engineering students as subjects. <strong>Results</strong>: The subjects of BPMN group found more accidents, hazards as well as more causes of hazards. Moreover, they have a higher preference for the template used for safety analysis documentation. <strong>Conclusions</strong>: The use of BPMN to represent the interactions among actors in a system probably lead to the discovery of more accidents and hazards, but more experiments are necessary to test this hypothesis since the results are not statistically significant.</p>
An Empirical Evaluation about Using Models to Improve Preliminary Safety Analysis - MSSIS 2020
<p>Video presentation of the paper "<em>An Empirical Evaluation about Using Models to Improve Preliminary Safety Analysis</em>" to appear at <strong>II Workshop de Modelagem e Simulação de sistemas intensivos em Software (II MSSiS) </strong>2020 co-located with CBSOFT 2020.</p> <p><strong>Abstract.</strong> <strong>Context</strong>: Safety analysis is an activity of fundamental importance in the development of safety-critical systems (SCS) to ensure that hazardous situations are properly found and mitigated. Such analysis is performed after a system requirements specification is available. Therefore, it is then worthwhile to investigate specification techniques to detect their strengths and weaknesses with respect to discovering hazards early in the development process. <strong>Objective</strong>: In this paper, we investigate similarities and differences in the results of a preliminary safety analysis from requirements specified using models in Business Process Modeling Notation (BPMN) and Textual Use Cases (TUC). <strong>Method</strong>: We adopted a controlled experiment as research method using computer engineering students as subjects. <strong>Results</strong>: The subjects of BPMN group found more accidents, hazards as well as more causes of hazards. Moreover, they have a higher preference for the template used for safety analysis documentation. <strong>Conclusions</strong>: The use of BPMN to represent the interactions among actors in a system probably lead to the discovery of more accidents and hazards, but more experiments are necessary to test this hypothesis since the results are not statistically significant.</p>
Dataset accompanying paper submission for "Toward data-driven generation and evaluation of model structure for integrated representations of human behavior in water resources systems"
<p>This data set accompanies code archived at DOI: <a href="https://doi.org/10.5281/zenodo.3833186">10.5281/zenodo.3833186</a>, which was used in the experiments for the paper submission "Toward data-driven generation and evaluation of model structure for integrated representations of human behavior in water resources systems"</p>
Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review (Article Pool)
<p>This pdf includes all of the articles that analyzed in the study: "Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review".</p>
Evaluation of the silkworm lemon mutant as an invertebrate animal model for human sepiapterin reductase deficiency
Human sepiapterin reductase deficiency is an inherited disease caused by SPR gene mutations and is a monoamine neurotransmitter disorder. Here, we investigated whether the silkworm lemon mutant could serve as a model of sepiapterin reductase deficiency. A point mutation in the BmSPR gene led to a five amino acid deletion at the carboxyl terminus in the lemon mutant. In addition, classical phenotypes seen in sepiapterin reductase deficient patients were observed in the lemon mutant, including a normal phenylalanine level, a decreased dopamine and serotonin content, and an increased neopterin level. A recovery test showed that replenishment of L-dopa significantly increased the dopamine level in the lemon mutant. The silkworm lemon mutant also showed negative behavioral abilities. These results suggest that the silkworm lemon mutant has an appropriate genetic basis and meets the biochemical requirements to be a model of sepiapterin reductase deficiency. Thus, the silkworm lemon mutant can serve as a candidate animal model of sepiapterin reductase deficiency, which may be helpful in facilitating accurate diagnosis and effective treatment options of sepiapterin reductase deficiency.
Data from: Evaluating population viability and efficacy of conservation management using integrated population models
Predicting population responses to environmental conditions or management scenarios is a fundamental challenge for conservation. Proper consideration of demographic, environmental and parameter uncertainties is essential for projecting population trends and optimal conservation strategies. We developed a coupled integrated population model-Bayesian population viability analysis to assess the (1) impact of demographic rates (survival, fecundity, immigration) on past population dynamics; (2) population viability 10 years into the future; and (3) efficacy of possible management strategies for the federally endangered Great Lakes piping plover Charadrius melodus population. Our model synthesizes long-term population survey, nest monitoring and mark–resight data, while accounting for multiple sources of uncertainty. We incorporated latent abundance of eastern North American merlins Falco columbarius, a primary predator of adult plovers, as a covariate on adult survival via a parallel state-space model, accounting for the influence of an imperfectly observed process (i.e. predation pressure) on population viability. Mean plover abundance increased from 18 pairs in 1993 to 75 pairs in 2016, but annual population growth (math formula) was projected to be 0.95 (95% CI 0.72–1.12), suggesting a potential decline to 67 pairs within 10 years. Without accounting for an expanding merlin population, we would have concluded that the plover population was projected to increase (math formula = 1.02; 95% CI 0.94–1.09) to 91 pairs by 2026. We compared four conservation scenarios: (1) no proposed management; (2) increased control of chick predators (e.g. Corvidae, Laridae, mammals); (3) increased merlin control; and (4) simultaneous chick predator and merlin control. Compared to the null scenario, chick predator control reduced quasi-extinction probability from 11.9% to 8.7%, merlin control more than halved (3.5%) the probability and simultaneous control reduced quasi-extinction probability to 2.6%. Synthesis and applications. Piping plover recovery actions should consider systematic predator control, rather than current ad hoc protocols, especially given the predicted increase in regional merlin abundance. This approach of combining integrated population models with Bayesian population viability analysis to identify limiting components of the population cycle and evaluate alternative management strategies for conservation decision-making shows great utility for aiding recovery of threatened populations.
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.