Crowdsourcing is a multidisciplinary research area in-cluding disciplines like artificial intelligence, human-computer interaction, database, and social science. One of the main objectives of AAAI HCOMP conferences is to bring together researchers from different fields and provide them opportunities to exchange ideas and share new research results. To facilitate cooperation across disciplines,repro-ducibilityis a crucial factor, but unfortunately it has not got-ten enough attention in the HCOMP community.
This article describes a series of experiments on gender attribution of Polish texts. The research was conducted on the publicly available corpus called "He Said She Said", consisting of a large number of short texts from the Polish version of Common Crawl. As opposed to other experiments on gender attribution, this research takes on a task of classifying relatively short texts, authored by many different people. For the sake of this work, the original "He Said She Said" corpus was filtered in order to eliminate noise and apparent errors in the training data. In the next step, various machine learning algorithms were developed in order to achieve better classification accuracy. Interestingly, the results of the experiments presented in this paper are fully reproducible, as all the source codes were deposited in the open platform Gonito.net. Gonito.net allows for defining machine learning tasks to be tackled by multiple researchers and provides the researchers with easy access to each other’s results.
The study of diet quality in a population provides information for the development of programs to improve nutritional status through better directed actions. The aim of this study was to assess the reproducibility and relative validity of a Mexican Diet Quality Index (ICDMx) for the assessment of the habitual diet of adults.
Reproducibility is receiving increased attention across many domains of science and genomics is no exception. Efforts to identify copy number variations (CNVs) from exome sequence (ES) data have been increasing. Many algorithms have been published to discover CNVs from exomes and a major challenge is the reproducibility in other datasets. Here we test exome CNV calling reproducibility under three conditions: data generated by different sequencing centers; varying sample sizes; and varying capture methodology.
Standardized, reproducible, and feasible quantification ofb-cell function (BCF) is necessary for the evaluation of interventions to improve insulin secretion and important for comparison across studies. We therefore characterized the re-sponses to, and reproducibility of, standardized methods of in vivo BCF across different glucose tolerance states. Reproducibility for the AST was very good, with ICC values >0.8 across all variables and populations.
The concept of reproducibility is a foundation of the scientific method. With the arrival of fast and powerful computers over the last few decades, there has been an explosion of results based on complex computational analyses and simulations. The reproducibility of these results has been addressed mainly in terms of exact replicability or numerical equivalence, ignoring the wider issue of the reproducibility of conclusions through equivalent, extended or alternative methods.