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25 results for “Predictive Skills”
Datasets from study: "Land surface observations boost temperature forecast skill: experiments using Long Short-Term Memory surrogate for physics-based models to assess potential predictability"
<p>This repository contains the datasets needed to reproduce the figures from manuscript: Land surface observations boost temperature forecast skill: experiments using Long Short-Term Memory surrogate for physics-based models to assess potential predictability.</p> <p>In this study, we examine the potential of land surface temperature and vegetation data, which are not routinely assimilated in NWP models, for enhancing temperature forecast skill. We build surrogate models for NWP using Long Short-Term Memory.</p>
Data archive and code for "Predicting September Arctic Sea Ice: A Multi-Model Seasonal Skill Comparison"
<p>This upload contains data and code related to the paper "Predicting September Arctic Sea Ice: A Multi-Model Seasonal Skill Comparison" by M. Bushuk, S. Ali, D. Bailey, Q. Bao, L. Batte, U. S. Bhatt, E. Blanchard-Wrigglesworth, E. Blockley, G. Cawley, J. Chi, F. Counillon, P. Goulet Coulombe, R. Cullather, F. X. Diebold, A. Dirkson, E. Exarchou, M. Gobel, W. Gregory, V. Guemas, L. Hamilton, B. He, S. Horvath, M. Ionita, J. E. Kay, E. Kim, N. Kimura, D. Kondrashov, Z. M. Labe, W. Lee, Y. J. Lee, C. Li, X. Li, Y. Lin, Y. Liu, W. Maslowski, F. Massonnet, W. N. Meier, W. J. Merryfield, H. Myint, J. C. Acosta Navarro, A. Petty, F. Qiao, D. Schroder, A. Schweiger, Q. Shu, M. Sigmond, M. Steele, J. Stroeve, N. Sun, S. Tietsche, M. Tsamados, K. Wang, J. Wang, W. Wang, Y. Wang, Y. Wang, J. Williams, Q. Yang, X. Yuan, J. Zhang, and Y. Zhang, published in the Bulletin of the American Meteorological Society, DOI: https://doi.org/10.1175/BAMS-D-23-0163.1.</p> <p>See README.txt for a description of the datasets and code.</p>
Interception of virtual throws reveals predictive skills based on the visual processing of throwing kinematics - Dataset
<p>Dataset consists of a list of Matlab structures, one for each of the 21 participants. For each participant all the recorded trials are reported ("trials" field). For each trial, the dataset reports information about the associated experimental condition and the kinematics of the ball and the racket trajectories. Information about the experimental condition are specified in the "info" field, which provides the experimental phase (Training and Experimental), the visibility (AllVisible, ThrowerOnly, BallOnly), the target (1, 2, 3, 4), and the thrower ID (1, 2, 3, 4). The kinematics data, starting from the time of ball release, are given in the field "trajectories", which provides the time vector (in seconds), and the corresponding 3D positions of the racket and the ball (in meters) in the reference frame shown in Figure 1 of the paper.</p>
Dataset of Intention to Whistleblow: Perception of Reporting Skill Mediates the Predicting Role of Class Consciousness and Perceived Probability of Revenge
<p><em>Dataset of </em><strong>Intention to Whistleblow: Perception of Reporting Skill Mediates the Predicting Role of Class Consciousness and Perceived Probability of Revenge</strong></p>
Exceptional multi-year prediction skill of the Kuroshio Extension in the high-resolution CESM decadal prediction system
The Kuroshio Extension (KE) has far-reaching influences on climate as well as on local marine ecosystems. Thus, skillful multi-year to decadal prediction of the KE state and understanding sources of skill are valuable. Retrospective forecasts using the high-resolution CESM show exceptional skill in predicting KE variability up to lead year 4, substantially higher than the skill found in a similarly configured low-resolution CESM. The higher skill is attained because the high-resolution system can more realistically simulate the westward Rossby wave propagation of initialized ocean anomalies in the central North Pacific and their expression within the sharp KE front, and does not suffer from spurious variability near Japan present in the low-resolution CESM that interferes with the incoming wave propagation. These results argue for the use of high-resolution models for future studies that aim to predict changes in western boundary current systems and associated biological fields.
Data and Code for Yeager et al., 2022: Enhanced Skill and Signal-to-noise in an Eddy-Resolving Decadal Prediction System
The sensitivity of decadal prediction system performance to model resolution is examined by comparing results from low- and high-resolution (LR and HR) predictions conducted with the Community Earth System Model (CESM). The primary difference between the two systems is the horizontal grid spacing of the ocean and atmosphere models (1° for both in LR; 0.1° and 0.25°, respectively, in HR), permitting a first direct comparison of how skill and signal-to-noise characteristics change when moving to the ocean eddy-resolved modeling regime. HR exhibits significantly increased skill and enhanced signal-to-noise for atmospheric fields compared to LR. This result suggests that mesoscale atmosphere-ocean interaction, which is present in HR but absent in LR, is a key mechanism involved in the transmission of predictable signals from the ocean to the atmosphere. Climate predictions can potentially be improved (and the signal-to-noise paradox alleviated) through explicit representation of ocean eddies and their interactions with the atmosphere.
Problem-solving skills are predicted by innovations in the wild and brain size in Passerines
<p>Code and dataset for the article "<strong>Problem-solving skills are predicted by innovations in the wild and brain size in Passerines</strong>"</p>
Job Prediction based on Skills and Years of experience
<h2><strong>Purpose:</strong></h2><p>This dataset was meticulously collected by me during my academic journey. It comprises information on various attributes related to individuals' academic backgrounds, programming skills, work experiences, and roles in the field of technology. The dataset is specifically designed for job prediction purposes, helping to analyze and forecast potential job roles based on individuals' qualifications.</p>
Skillful decadal UK flood prediction - DO NOT USE
<p>The scripts in this repository perform the analysis shown in the manuscript "Skillful decadal UK flood prediction" by Moulds et al., which is currently under consideration in Geophysical Research Letters.</p>
Data and software from: Decomposition of skill scores for conditional verification – Impact of AMO phases on the predictability of decadal temperature forecasts
<p>Data and software from "Decomposition of skill scores for conditional verification – Impact of AMO phases on the predictability of decadal temperature forecasts"</p> <ul> <li>synthetic data and score computation routine</li> <li>data from MiKlip decadal prediction systems preop-dcpp-HR, preop-LR and observational HadCRUT4 data used for the conditional verification</li> <li>AMO calculation routine</li> <li>AMO data and phases defining the ocean state used in the conditional verification</li> </ul> <p>The computation routines from the conditional verification of decadal predcition systems is publicly available as the Freva plug-in "ProblEMS" at <a href="https://doi.org/10.5281/zenodo.10469658">https://doi.org/10.5281/zenodo.10469658</a></p> <p> </p>
A multi-model ensemble of baseline and process-based models improves the predictive skill of near-term lake forecasts: data, forecasts, and scores
<p>This data publication contains zipped parquet from the Falling Creek Reservoir multi-model ensemble (MME) forecasting work using the FLARE (Forecasting Lake And Reservoir Ecosystems) system and baseline models: drivers.zip contains NOAA driver forecast files, targets.zip contains in-situ water temperature observations, forecasts.zip contains forecast parquet files generated from the MME workflow (FLARE & baseline models), and scores.zip contains forecast skill metrics required for analysis.</p>
Skillful Seasonal Prediction of Wind Energy Resources in the contiguous United States
<p>This dataset contains data files used to replicate figures in a paper published in communications earth & environment. These datasets are in .mat format, which can be readable by Matlab software.</p>
The angle of attack: Rapping technique predicts skill in hermit crab contests
<p>Skill, the ability to perform a challenging behaviour well, has been shown to be an important determinant of success in a variety of contexts, including human sports, animal courtship and most recently, animal contests. Because skilful movement requires precise motor control, skill is assumed to be underpinned by traits that determine these abilities. However, while these traits determine an individual's potential to perform skilful movements (known as technique), this potential may not translate into skilful fighting due to interference from the opponent. Here, we investigate the relationship between technique and skill using the European hermit crab <i>Pagurus bernhardus</i>. By examining the spatial distribution of shell raps, we find that on average, technique exhibited during a "training" fight predicts the level of skill displayed in a real contest. However, our results also demonstrate substantial among-individual variation in the direction of change across the two fights, with some individuals exhibiting better technique than skill and others showing the opposite pattern. Finally, we find that winners, but not losers, progressively adapt their targeting of strikes when faced with a fully functional opponent. Our results indicate that skill is a combination of innate technique and the ability to adapt to an opponent's behaviour.</p>
Foraging on anthropogenic food predicts problem-solving skills in a seabird
<p>Species and populations with greater cognitive performance are more successful at adapting to changing habitats. Accordingly, urban species and populations often outperform their rural counterparts on problem-solving tests. Paradoxically, urban foraging also might be detrimental to the development and integrity of animals' brains because anthropogenic foods often lack essential nutrients such as the long-chain omega-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), which are important for cognitive performance in mammals and possibly birds. We tested whether urbanization or consumption of EPA and DHA are associated with problem-solving abilities in ring-billed gulls, a seabird that historically exploited marine environments rich in omega-3 fatty acids but now also thrives in urban centres. Using incubating adults nesting across a range of rural to urban colonies with equal access to the ocean, we tested whether urban gulls preferentially consumed anthropogenic food while rural nesters relied on marine organisms. As we expected individual variation in foraging habits within nesting location, we characterized each captured gulls' diet using stable isotope and fatty acid analyses of their red blood cells. To test their problem-solving abilities, we presented the sampled birds with a horizontal rendition of the string-pull test, a foraging puzzle often used in animal cognitive studies. The isotopic and fatty acid profiles of urban nesters indicated a diet comprising primarily anthropogenic food, whereas the profiles of rural nesters indicated a high reliance on marine organisms. Despite the gulls' degree of access to urban foraging habitat not predicting solving success, birds with biochemical profiles reflecting anthropogenic food (less DHA and a higher carbon-13 ratio in their red blood cells) had a greater probability of solving the string-pull test. These results suggest that experience foraging on anthropogenic food is the main explanatory factor leading to successful problem-solving, while regular consumption of omega-3s during incubation appears inconsequential.</p>
Skillful decadal flood prediction
<p>Data and scripts required to reproduce the analysis described in the Geophysical Research Letters journal article <em>Skillful decadal flood prediction</em> (<a href="https://doi.org/10.1029/2022GL100650">https://doi.org/10.1029/2022GL100650</a>).</p>
Mindfulness and Executive Functions for Prediction of Non-technical Skills of Students in Pediatric Medical Simulations
ClinicalTrials.gov study NCT03761355. IPD Sharing: UNDECIDED. Countries: 1. Publications: 7.
Foraging on anthropogenic food predicts problem-solving skills in a seabird
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Data from: Seasonality modulates the predictive skills of diatom based salinity transfer functions
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The angle of attack: Rapping technique predicts skill in hermit crab contests
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Data from: Skill not athleticism predicts individual variation in match performance of soccer players
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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.