reprohack / reprohack-2019-06-27 Goto Github PK
View Code? Open in Web Editor NEWHome Page: https://sheffield-university.shinyapps.io/ReproHack_CCMcr/
Home Page: https://sheffield-university.shinyapps.io/ReproHack_CCMcr/
From the abstract: "In this article I present a reproducible review of recent research to investigate the spatial positioning of neurons in the nervous system"
paper URL:
data URL:
code URL: https://github.com/sje30/eglen2015
reproduction/replication URL:
Comparing data collection methods as tools for assessing diversity across urban landscapes
paper URL:
https://doi.org/10.3390/insects9040186
data URL:
https://doi.org/10.5281/zenodo.1436741
code URL:
https://doi.org/10.5281/zenodo.1436741
reproduction/replication URL:
paper URL: https://doi.org/10.1039/c9cp00203k
data URL: https://doi.org/10.15125/BATH-00548
code URL: https://doi.org/10.5281/zenodo.2577796
reproduction/replication URL:
Comparing theory-driven and data-driven attractiveness models using images of real women’s faces by Holzleitner et al. (in press) JEP:HPP.
This paper contrasts the top down (i.e., theory driven) with bottom up (i.e., data driven) models of attractiveness judgements (provided by an independent group of raters). The top down approach used a number of components (e.g., facial asymmetry) that were objectively designed and measured (and were chosen due to their prevalence in theories of facial attractiveness). The data driven approach was entirely bottom-up and theory-independent. For both the group of theory-driven models and the data-driven model, rated attractiveness was the outcome measure with (for the theory-driven models) subsets of the objective measures (e.g., facial asymmetry) as predictors. Goodness-of-fit of each model was measured using root-mean-square error (RMSE) with (overall) the data-driven approach explaining more variability in the data (relative to the top-down only model). Additionally, the data-driven model had the lowest AIC indicating that even with additional predictors, the explanatory performance of the model was sufficiently improved to justify the inclusion of the full range of predictors.
Paper URL: https://psyarxiv.com/vhc5k
Data URL: https://osf.io/jurcq/
Code URL: https://osf.io/jurcq/
Using a Bayesian inference approach to evaluate asymptotic behaviour by sampling finite simulated trajectories.
data URL: ftp://ftp.aip.org/epaps/journ_chem_phys/E-JCPSA6-145-039640
code URL: ftp://ftp.aip.org/epaps/journ_chem_phys/E-JCPSA6-145-039640
reproduction/replication URL:
Title: Evaluation of App-Embedded Disease Scales for Aiding Visual Severity Estimation of Cercospora Leaf Spot of Table Beet
Paper URL: https://apsjournals.apsnet.org/doi/10.1094/PDIS-10-18-1718-RE
Data URL: https://osf.io/ezxps/
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.