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31
datasets available to search
ShareScore release 0.9.0
Dataset results
31 results for “Reproducible Research”
Data to reproduce the results presented in de Lange et al. 2023. Water Resources Research, "The Impact Of Flocculation on In Situ and Ex Situ Particle Size Measurements by Laser Diffraction"
<p>This repository consists data to reproduce results as presented in: "The Impact Of Flocculation on In Situ and Ex Situ Particle Size Measurements by Laser Diffraction", Water Resources Research. Kindly refer to the readme.text file to navigate through the dataset.</p>
Teaching Data Set for Reproducible Research
<p>I use this data set in teaching settings.</p>
pyKNEEr: An image analysis workflow for open and reproducible research on femoral knee cartilage - Validation data
<p>Image data used in the paper introducing pyKNEEr. Explanations about these data are in the <a href="https://github.com/sbonaretti/pyKNEEr/tree/master/publication">GitHub</a> repository</p> <p>Changes in version 0.2.0: </p> <p>- Added inHouse images </p> <p>- Segmented images casted to int16 for smaller file size</p>
Evaluating the method reproducibility of deep learning models in the biodiversity research
Open the record for dataset details and reuse information.
Data to reproduce the results presented in Sehgal et al. 2022. Journal of Geophysical Research Earth Surface, https://doi.org/10.1029/2022JF006838 ("A Generic Relation Between Turbidity, Suspended Particulate Matter Concentration, and Sediment Characteristics")
<p>This repository consists data to reproduce results as presented in: "A Generic Relation Between Turbidity, Suspended Particulate Matter Concentration, and Sediment Characteristics", Journal of Geophysical Research Earth Surface. Kindly refer to the readme.text file to navigate through the dataset.</p>
Figure 3 from: Leonard J, Flournoy J, Lewis-de los Angeles CP, Whitaker K (2017) How much motion is too much motion? Determining motion thresholds by sample size for reproducibility in developmental resting-state MRI. Research Ideas and Outcomes 3: e12569. https://doi.org/10.3897/rio.3.e12569
Figure 3 - Out of sample prediction accuracy of autism diagnosis using resting state data as a function of sample size and motion-based exclusion criteria (percentage of fMRI, whole-brain volumes exceeding threshold). Red line is a naive classifier that assumes that all participants share the modal diagnosis (in this case, non-ASD). The black line spans the 5th to 95th percentile accuracy across iterations using a linear SVM, with the black points at the median value. Code and output can be found on GitHub (Flournoy and Leonard 2017).
Figure 2 from: Leonard J, Flournoy J, Lewis-de los Angeles CP, Whitaker K (2017) How much motion is too much motion? Determining motion thresholds by sample size for reproducibility in developmental resting-state MRI. Research Ideas and Outcomes 3: e12569. https://doi.org/10.3897/rio.3.e12569
Figure 2 - Split-half reliability results showing how sample size (N) has a large effect on R squared (median R squared from 100 permutations) while motion threshold does not. Error bars represent average 95% confidence intervals across 100 permutations. Code and output can be found on GitHub (Flournoy and Leonard 2017).
Figure 1 from: Leonard J, Flournoy J, Lewis-de los Angeles CP, Whitaker K (2017) How much motion is too much motion? Determining motion thresholds by sample size for reproducibility in developmental resting-state MRI. Research Ideas and Outcomes 3: e12569. https://doi.org/10.3897/rio.3.e12569
Figure 1 - In order to investigate the effects of age range, motion exclusion threshold and sample size on functional connectiivity reliability we split the data into two matched samples. For the reliability analysis we averaged all participants in each sample and then calculated how well aligned the two groups were in terms of each pairwise regional connectivity measure. For the out-of-sample prediction analysis we used one half of the data to train a model and then tested it on the other half.
Data from: The reproducibility of research and the misinterpretation of p-values
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Routine Validation and Reproducibility Testing of Laboratory Assays and Research Techniques Used for Endocrine, Cardiometabolic, and Musculoskeletal Disorder Research (VALD)
ClinicalTrials.gov study NCT07083557. IPD Sharing: NO. Countries: 1. Publications: 0.
Routine Validation and Reproducibility Testing of Laboratory Measures and Research Techniques Used for Metabolism Research (VAL)
ClinicalTrials.gov study NCT06286761. IPD Sharing: NO. Countries: 1. Publications: 0.
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.