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.
30
datasets available to search
ShareScore release 0.9.0
Dataset results
30 results for “code mixing”
parallelpro/numax: Source code for "Realistic Uncertainties for Fundamental Properties of Asteroseismic Red Giants and the Interplay Between Mixing Length, Metallicity and Numax" by Li, Yaguang et al. (2024)
<p>This repository contains the datasets and Python scripts used in the paper "Realistic Uncertainties for Fundamental Properties of Asteroseismic Red Giants and the Interplay Between Mixing Length, Metallicity, and Numax" by Yaguang Li et al. (2024). The stellar models used in this project are available on <a href="https://doi.org/10.5281/zenodo.12815718">Zenodo</a>.</p>
Code and Data for "Global Surface Eddy Mixing Ellipses: Spatio-temporal Variability and Machine Learning Prediction" By Jing et al. Submitted to Journal of Geophysical Research: Oceans.
<p>This repository contains the code and data for the study of "Global Surface Eddy Mixing Ellipses: Spatio-temporal Variability and Machine Learning Prediction" By Jing et al. Submitted to Journal of Geophysical Research: Oceans.</p> <p>Specifically, this repository contains the following items: </p> <p>(1) The codes needed for assessing the representation and prediction skills of Random Forest (RF) and Convolutional Neural Network (CNN) models. </p> <p>(2) Original and normalized data to run these codes.</p> <p>(3) Code here is built on early work from our laboratory (Guan et al., 2022; Zhang et al., 2023), though great modifications have been made tailored to our scientific question.</p> <div>[1] Guan, W., Chen, R., Zhang, H., Yang, Y., & Wei, H. (2022). Seasonal surface eddy mixing in the Kuroshio Extension: Estimation and machine learning prediction. Journal of Geophysical Research: Oceans, 127 (3), e2021JC017967.</div> <div>[2] Zhang, G., Chen, R., Li, X., Li, L., Wei, H., & Guan, W. (2023). Temporal variability of global surface eddy diffusivities: Estimates and machine learning prediction. Journal of Physical Oceanography, 53 (7), 1711–1730.</div>
Dataset and codes used in the manuscript entitled "A rainfall-tracking travel time distribution model to quantify mixing and storage release preference in a large shallow lake by two-year stable isotopic data"
<p>This contains the codes and dataset for the manuscript entitled "A rainfall-tracking travel time distribution model to quantify mixing and storage release preference in a large shallow lake by two-year stable isotopic data". Detailed information about the dataset is described in the Readme.txt file.</p>
Dataset and code for the manuscript 'Parameterizing Vertical Mixing Coefficients in the Ocean Surface Boundary Layer using Neural Networks'
<p>This repository contains the code and data used in the manuscript 'Parameterizing Vertical Mixing Coefficients in the Ocean Surface Boundary Layer using Neural Networks'. <br> Manuscript authors: Dr. Aakash Sane, Dr. Brandon G. Reichl, Dr. Alistair Adcroft, Dr. Laure Zanna<br> Manuscript preprint link: https://doi.org/10.48550/arXiv.2306.09045</p>
Mixed body- and gaze-centered coding of proprioceptive reach targets after effector movement
<p>Previous studies demonstrated that an effector movement intervening between encoding and reaching to a proprioceptive target determines the underlying reference frame: proprioceptive reach targets are represented in a gaze-independent reference frame if no movement occurs but are represented with respect to gaze after an effector movement (Mueller and Fiehler, 2014a). The present experiment explores whether an effector movement leads to a switch from a gaze-independent, body-centered reference frame to a gaze-dependent reference frame or whether a gaze-dependent reference frame is employed in addition to a gaze-independent, body-centered reference frame. Human participants were asked to reach in complete darkness to an unseen finger (proprioceptive target) of their left target hand indicated by a touch. They completed 2 conditions in which the target hand remained either stationary at the target location (stationary condition) or was actively moved to the target location, received a touch and was moved back before reaching to the target (moved condition). We dissociated the location of the movement vector relative to the body midline and to the gaze direction. Using correlation and regression analyses, we estimated the contribution of each reference frame based on horizontal reach errors in the stationary and moved conditions. Gaze-centered coding was only found in the moved condition, replicating our previous results. Body-centered coding dominated in the stationary condition while body- and gaze-centered coding contributed equally strong in the moved condition. Our results indicate a shift from body-centered to combined body- and gaze-centered coding due to an effector movement before reaching towards proprioceptive targets.</p>
Data and code for: "Mixed evidence for species diversity affecting ecological forecasts in constant versus declining light "
<p>Data and code for the article "<strong><span>Mixed evidence for species diversity affecting ecological forecasts in constant versus declining light </span></strong>"</p>
Attributing agnostically-detected large reductions in road CO2 emissions to policy mixes (code and data)
<p>Data and code to reproduce the main results of the paper.</p>
Code and data for 'Alpha, beta and gamma diversity in intact, mixed and transformed landscapes'
<p>The data and scripts in this database are analyses for a research:<strong> </strong>Alpha, beta and gamma diversity in intact, mixed and transformed landscapes. Please refer to the README file and the paper for details about the usage of the data and methodology.</p> <p>Software: R 4.1.0</p>
Code and data for reproducing results in P.Vacek, H. Anzt, E. Carson, N. Kohl, U. Rüde and Y.-H. Tsai: Mixed precision multigrid with smoothing based on incomplete Cholesky factorization (2024).
<p>Code and data for reproducing results in P.Vacek, H. Anzt, E. Carson, N. Kohl, U. Rüde and Y.-H. Tsai: Mixed precision multigrid with smoothing based on incomplete Cholesky factorization (2024). </p> <p>The repository contains MATLAB codes as well as a snapshot of a [Ginkgo Library repository](https://github.com/ginkgo-project/ginkgo), used for generating the results presented in the paper.</p>
Model code and Data for manuscript 'The Role of Wave-induced Mixing in Spring Phytoplankton Bloom in the South Yellow Sea'
<p>This repository contains four files:</p> <p>(1) Wave-induced mixing data for China seas;</p> <p>(2) Water transparency data for the South Yellow Sea;</p> <p>(3) Observation data used in this study; and</p> <p>(4) Model code for our ecological model and model experiments, including configuration data file. </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.