The replicability crisis in the social, behavioral, and data sciences has led to the formulation
of algorithm frameworks for replicability---ie, a requirement that an algorithm produce …

Reproducibility of experiments is a complex task in stochastic methods such as evolutionary
algorithms or metaheuristics in general. Many works from the literature give general …

Replication studies in computational communication science (CCS) play a vital role in
upholding research validity, ensuring reliability, and promoting transparency. However …

Despite recent calls to make geographical analyses more reproducible, formal attempts to
reproduce or replicate published work remain largely absent from the geographic literature …

Reproducibility is widely acknowledged as a fundamental principle in scientific research.
Currently, the scientific community grapples with numerous challenges associated with …

This educational article explores the convergence of open science practices and traditional,
complementary, and integrative medicine (TCIM), shedding light on the potential benefits …

Missing or inaccessible information about the methods used in scientific research slows the
pace of discovery and hampers reproducibility. Yet little is known about how, why, and under …

Feature selection (FS) stability is an important topic of recent interest. Finding stable features
is important for creating reliable, non-overfitted feature sets, which in turn can be used to …

The idea of reproducibility is one that has gained much attention in the field of data analysis
in recent years–for example, Buckheit and Donoho (1995), Peng (2011) and Stodden …

This paper presents maxent. ot, a package for doing phonological analysis using Maximum
Entropy Optimality Theory written in the statistical programming language R. R has become …