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184
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Dataset results
184 results for “Replication Study”
Semi-replicate Crossover Bioequivalence Study of Dirithromycin in Healthy Subjects Under Fed Conditions
ClinicalTrials.gov study NCT02237807. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Safety Study of Replication-competent Adenovirus (Delta-24-rgd) in Patients With Recurrent Glioblastoma
ClinicalTrials.gov study NCT01582516. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Single Dose, 4-Period, 2-Treatment Replicate Design Bioequivalency Study of Granisetron Hydrochloride 1 mg Tablets Under Fed Conditions
ClinicalTrials.gov study NCT00618111. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Long-term Follow-up Study of Patients Who Received EG110A, a Non-replicative Herpes Simplex Virus 1-derived Gene Therapy
ClinicalTrials.gov study NCT07227285. IPD Sharing: NO. Countries: 1. Publications: 0.
Systematic meta-analysis and replication of genome-wide expression studies identifies molecular pathways of Parkinson’s disease
GEO Series GSE24378. Homo sapiens. 17 samples. Type: Expression profiling by array.
Dynamic changes in liver 5-hydroxymethylcytosine profiles upon non-genotoxic carcinogen exposure [Replicated control vs. pb treated study]
GEO Series GSE45465. Mus musculus. 39 samples. Type: Expression profiling by array.
Systematic meta-analysis and replication of genome-wide expression studies of Parkinson’s disease: 4
GEO Series GSE20314. Homo sapiens. 8 samples. Type: Expression profiling by array.
Systematic meta-analysis and replication of genome-wide expression studies of Parkinson's disease
GEO Series GSE20186. Homo sapiens. 69 samples. Type: Expression profiling by array.
Systematic meta-analysis and replication of genome-wide expression studies of Parkinson's disease: 3
GEO Series GSE20164. Homo sapiens. 11 samples. Type: Expression profiling by array.
Teen Pregnancy Prevention Replication Study
ClinicalTrials.gov study NCT02540304. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Preschool First Step to Success: An Efficacy Replication Study
ClinicalTrials.gov study NCT03729154. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Replication Study to Analyze the Surgical Treatment of Proximal Humeral Fracture
ClinicalTrials.gov study NCT06537024. IPD Sharing: NO. Countries: 0. Publications: 0.
A Study of the Safety of Toca 511, a Retroviral Replicating Vector, Combined With Toca FC in Subjects With Newly Diagnosed High Grade Glioma Receiving Standard of Care
ClinicalTrials.gov study NCT02598011. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Systematic meta-analysis and replication of genome-wide expression studies of Parkinson's disease: 2
GEO Series GSE20163. Homo sapiens. 17 samples. Type: Expression profiling by array.
Replication package of paper 'Study of IoT System Architectural Styles and their Quality Requirements'
<p>Dataset of studied papers.</p> <p>It contains an Excel sheet that includes papers selected in each step of our selection process, along with the extracted data in each tab.</p>
Database publication - To Replicate, or Not to Replicate? The Creation, Use, and Dissemination of 3D Models of Human Remains: A Case Study from Portugal, Heritage 2022, 5,
<p>This database contains the data used in the manuscript - Alves-Cardoso, F.A.; Campanacho, V. To Replicate, or Not to Replicate? The Creation, Use, and Dissemination of 3D Models of Human Remains: A Case Study from Portugal. <em>Heritage </em><strong>2022</strong>, <em>5</em></p> <p>Abstract:</p> <p>Advancements in digital technology have conquered a place in cultural heritage. The widespread use of three-dimensional scanners in bioanthropology have increased the production of 3D digital replicas of human bones that are freely distributed online. However, ethical considerations about such 3D models have not reached Portuguese society, making it impossible to assess their societal impact and people’s perception of how these models are created and used. Therefore, Portuguese residents were asked to take part in an online survey. The ratio of male to female participants was 0.5:1 in 312 contributors. The age ranged between 18 and 69 years. The majority had a higher education degree. Only 43% had seen a 3D model, and 43% considered the 3D replicas the same as real bone. Also, 87% would be willing to allow their skeleton and family members to be digitalized after death, and 64% advocated the controlled dissemination of replicas through registration and login and context description association (84%). Overall, the results suggest agreement in disseminating 3D digital replicas of human bones. On a final note, the limited number of participants may be interpreted as a lack of interest in the topic or, more importantly, a low self-assessment of their opinion on the subject.</p>
Replication Package for "A Characterization of Datasets for Vulnerability Prediction Studies"
<p>The present upload constitute the Replicability Package for the "A Characterization of Datasets for Vulnerability Prediction Studies" paper.</p>
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>
Replication Package for the Paper: "A Machine Learning Based Ensemble Method for Automatic Classification of Decisions: A Study of the Hibernate Developer Mailing List"
<p>This is the replication package for the paper: "A Machine Learning Based Ensemble Method for Automatic Classification of Decisions: A Study of the Hibernate Developer Mailing List". It contains the source code and dataset of our experiment for the replication by other researchers. In the meanwhile, we provide brief description of the files in the replication package below.</p> <p><strong>1. code folder</strong></p> <ul> <li><em>experiment.py </em>contains the source code for our experiment, which is conducted on Windows 10 and Python 3.7.0. <strong>Note that you may get slightly</strong> <strong>different experiment results when conducting the experiments on different environment configurations.</strong></li> <li><em>requirement.txt</em> records all the installation packages and their version numbers needed for the current program to run. You can use "<em>pip install -r requirement.txt</em>" to rebuild the project and install all dependencies. <strong>Note that you may get slightly different experiment results when using different packages or versions. </strong></li> </ul> <p><strong>2. dataset folder</strong></p> <ul> <li><em>decisions.xlsx </em>contains 844 labelled sentence-level decisions from the Hibernate developer mailing list.</li> </ul>
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.