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Dataset results
260 results for “, empirical studies”
An Empirical Study of Perceived Hospital Service Quality: A Comparison of Inpatient, Outpatient and Emergence Patient
ClinicalTrials.gov study NCT00950560. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Study to Evaluate the Clinical Outcome in High Risk Patients Who Received Empirical Antifungal Therapy
ClinicalTrials.gov study NCT01439646. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: Minimum sample sizes for population genomics: an empirical study from an Amazonian plant species
Open the record for dataset details and reuse information.
Data from: pLARmEB: integration of least angle regression with empirical Bayes for multilocus genome-wide association studies
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Influencing Factors on Preventive Health Behaviors: An Empirical Study on the Case of COVID-19 in China Based on the Situational Theory of Publics and Social Exchange Theory
<p>Data in the research</p>
The Cost of Build Tool Downgrades: An Empirical Study of the Kubernetes Project
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Literal interviews (The Mutual Influence between Entrepreneurial Marketing and Causal and Effectual Entrepreneurship: An Empirical Study in an Emerging and Developing Economy)
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Can LLMs Generate Higher Quality Code Than Humans? An Empirical Study
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Empirical Comparative Study of Variation Blood Level Antibody Vitamin D at Scleroderma (SSc) Patients Compared Healthy Peoples
ClinicalTrials.gov study NCT01553890. IPD Sharing: Not stated. Countries: 0. Publications: 0.
A Study of Empirical Antifungal Therapy With Itraconazole
ClinicalTrials.gov study NCT01706562. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Empirical Comperative Study Of Variation Blood Level Antibody Vitamin D at Different Groups Of Patients Compared Healthy Peoples
ClinicalTrials.gov study NCT02795234. IPD Sharing: Not stated. Countries: 0. Publications: 0.
A 28 - 90 Days Study to Evaluate the Safety, Tolerability, and Efficacy of Caspofungin Injection as Empirical Therapy in Indian Adults With Persistent Fever and Neutropenia (0991-053)(COMPLETED)
ClinicalTrials.gov study NCT00379964. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Architecture Decisions in Quantum Software Systems: An Empirical Study on Stack Exchange and GitHub
<p>This dataset was collected from GitHub and Stack Exchange (including Stack Overflow, Quantum Computing Stack Exchange, and Computer Science Stack Exchange) to conduct an empirical study on architecture decisions in quantum software systems. We provide below a brief description of each file:</p><p>1. Dataset (GitHub).xlsx</p><p>contains selected quantum software projects from GitHub with project names, issue IDs, and issue URLs and the data extracted from the GitHub issues that are related to architecture decisions in quantum software development.</p><p>2. Dataset (SO).xlsx</p><p>contains the IDs and URLs of Stack Overflow (SO) labeled posts and the extracted data from the Stack Overflow posts that are related to architecture decisions in quantum software development.</p><p>3. Dataset (QC).xlsx</p><p>contains the IDs and URLs of Quantum Computing (QC) Stack Exchange labeled posts and the extracted data from the Quantum Computing Stack Exchange posts that are related to architecture decisions in quantum software development.</p><p>4. Dataset (CS).xlsx</p><p>contains the IDs and URLs of Computer Science (CS) Stack Exchange labeled posts and the extracted data from the Computer Science Stack Exchange posts that are related to architecture decisions in quantum software development.</p><p>5. Extracted Data (GitHub+SO+QC+CS).xlsx</p><p>provides the final results of data extracted from the related GitHub issues, SO posts, QC posts, and CS posts.</p>
An Empirical Study of Deprecation Declarations in the Rust Ecosystem
<p><strong>An Empirical Study of Deprecation Declarations in the Rust Ecosystem</strong></p> <p>This Repository contains the data and scripts used in<em> An Empirical Study of Deprecation Declarations in the Rust Ecosystem</em>.</p> <p><strong>DataSet</strong>:</p> <ul> <li>crateio_dumps: It contains data related to Rust packages exported from <a href="https://crates.io/data-access">crate.io</a>.</li> <li>advisory-db: <ul> <li>GAD: GitHub Advisory Database, exported from <a href="https://github.com/github/advisory-database/tree/main/advisories/github-reviewed">reviewed adviosry-database repository</a>. </li> <li>RAD: RustSec Advisory Databa, exported from <a href="https://rustsec.org/">Rustsec advisories</a>.</li> </ul> </li> </ul> <p><strong>Scripts</strong>:</p> <ul> <li>0_preprocess.ipynb: Data preprocessing involves extracting dependency relationships between packages and filtering out the libraries for further study. </li> <li>1_RQ1.ipynb, 2_RQ1.ipynb: These two files obtains the results mentioned in RQ1.</li> <li>3_RQ2.ipynb: This file obtains the results mentioned in RQ2.</li> <li>4_RQ3.ipynb: This file obtains the results mentioned in RQ3.</li> </ul>
Empirical Data, Survey and Letter of Consent of the Study: Brouillet C. et al. "Soil extraction as an adaptation strategy to climate change - a focus on urban ecosystem services"
<ul> <li>Empirical Data (quantitative part of the results), Survey and Letter of Consent</li> <li>From the study entitled "Soil extraction as an adaptation strategy to climate change - a focus on urban ecosystem services" Brouillet C. et al. </li> <li>All documents are in French.</li> </ul>
Replication Package for the Paper: "Code Smells Detection via Code Review: An Empirical Study"
<p>This repository contains the data and results from the paper "Code Smells Detection via Code Review: An Empirical Study" submitted to ESEM 2020.</p> <p> </p> <p><strong>1. data folder</strong></p> <p>The data folder contains the retrieved 269 reviews that discuss code smells. Each review includes four parts: Code Change URL, Code Smell Term, Code Smell Discussion, and Source Code URL.</p> <p> </p> <p><strong>2. scripts floder</strong></p> <p>The scripts folder contains the Python script that was used to search for code smell terms and the list of code smell terms.</p> <ul> <li><em>smell-term/general_smell_terms.txt</em> contains general code smell terms, such as "code smell".</li> <li><em>smell-term/specific_smell_terms.txt</em> contains specific code smell terms, such as "dead code".</li> <li><em>smell-term/misspelling_terms_of_smell.txt</em> contains the misspelling terms of 'smell', such as "ssell".</li> <li><em>get_changes.py</em> is used for getting code changes from OpenStack.</li> <li><em>get_comments.py</em> is used for getting review comments for each code change.</li> <li><em>smell_search.py</em> is used for searching review comments that contain code smell terms.</li> </ul> <p> </p> <p><strong>3. project folder</strong></p> <p>The project folder contains the MAXQDA project files. The files can be opened by MAXQDA 12 or higher versions, which are available at https://www.maxqda.com/ for download. You may also use the free 14-day trial version of MAXQDA 2018, which is available at https://www.maxqda.com/trial for download.</p> <ul> <li><em>Data Labeling & Encoding for RQ2.mx12</em> is the results of data labeling and encoding for RQ2, which were analyzed by the MAXQDA tool.</li> <li><em>Data Labeling & Encoding for RQ3.mx12</em> is the results of data labeling and encoding for RQ3, which were analyzed by the MAXQDA tool.</li> </ul>
Replication Package for the Paper: "Code Smells Detection via Code Review: An Empirical Study"
<p>This repository contains the data and results from the paper "Code Smells Detection via Code Review: An Empirical Study" submitted to ESEM 2020.</p> <p> </p> <p><strong>1. data folder</strong></p> <p>The data folder contains the retrieved 269 reviews that discuss code smells. Each review includes four parts: Code Change URL, Code Smell Term, Code Smell Discussion, and Source Code URL.</p> <p> </p> <p><strong>2. scripts floder</strong></p> <p>The scripts folder contains the Python script that was used to search for code smell terms and the list of code smell terms.</p> <ul> <li><em>smell-term/general_smell_terms.txt</em> contains general code smell terms, such as "code smell".</li> <li><em>smell-term/specific_smell_terms.txt</em> contains specific code smell terms, such as "dead code".</li> <li><em>smell-term/misspelling_terms_of_smell.txt</em> contains the misspelling terms of 'smell', such as "ssell".</li> <li><em>get_changes.py</em> is used for getting code changes from OpenStack.</li> <li><em>get_comments.py</em> is used for getting review comments for each code change.</li> <li><em>smell_search.py</em> is used for searching review comments that contain code smell terms.</li> </ul> <p> </p> <p><strong>3. project folder</strong></p> <p>The project folder contains the MAXQDA project files. The files can be opened by MAXQDA 12 or higher versions, which are available at https://www.maxqda.com/ for download. You may also use the free 14-day trial version of MAXQDA 2018, which is available at https://www.maxqda.com/trial for download.</p> <ul> <li><em>Data Labeling & Encoding for RQ2.mx12</em> is the results of data labeling and encoding for RQ2, which were analyzed by the MAXQDA tool.</li> <li><em>Data Labeling & Encoding for RQ3.mx12</em> is the results of data labeling and encoding for RQ3, which were analyzed by the MAXQDA tool.</li> </ul>
The Impact of Continuous Integration into Test Code Evolution: An Empirical Study
<p>The set of datasets used during the study</p>
Dataset of An Empirical Study of Concurrency Vulnerabilities in Linux
<p>Dataset of An Empirical Study of Concurrency Vulnerabilities in Linux</p>
An Empirical Study of Embedded WebAssembly Virtual Machine
<p>This contains all the experimental code, data sets, and result files for our experiments.</p>
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.