Related papers: Risk and Scientific Reputation: Lessons from Cold …
Given the growing use of Artificial Intelligence (AI) and machine learning (ML) methods across all aspects of environmental sciences, it is imperative that we initiate a discussion about the ethical and responsible use of AI. In fact, much…
Scientific investigation procedures have been evolving to follow an ever-changing cultural landscape, the sophistication of the technology available and an ever-growing knowledge base. This continuous evolution brought investigation…
With the progressive digitalisation of a majority of services to communities and individuals, humankind is facing new challenges. While energy sources are rapidly dwindling and rigorous choices have to be made to ensure the sustainability…
Impact of science is one of the most important topics in scientometrics. Recent developments show a fundamental change in impact measurements from impact on science to impact on society. Since impact measurement is currently in a state of…
In a recent article, Falessi et al. (2017) call for a deeper understanding of the pros and cons of using students and professionals in experiments. The authors state: we have observed too many times that our papers were rejected because we…
Public-facing science communication is important in garnering interest, engagement, and trust in science. Social media platforms provide scientists with opportunities to reach broader audiences, yet many resist adopting social media writing…
This article attempts to discover the surreptitious features of ransomware and to address it in information systems security research. It intends to elicit attention with regard to ransomware, a newly emerged cyber threat using such…
Mountain river torrents and snow avalanches generate human and material damages with dramatic consequences. Knowledge about natural phenomenona is often lacking and expertise is required for decision and risk management purposes using…
The proliferation of AI-generated content online has fueled concerns over \emph{model collapse}, a degradation in future generative models' performance when trained on synthetic data generated by earlier models. Industry leaders, premier…
We are at the dawn of a new era, where advances in computer power, broadband communication and digital sensor technologies have led to an unprecedented flood of data inundating our surrounding. It is generally believed that means such as…
The promise of quantum computing is not speeding up conventional computing rather delivering an exponential advantage for certain classes of problems, with profound implications for cybersecurity for instance. With the advent and…
In most of the proposals for new physics beyond the standard model, neutrinos have new interactions and some of them have phenomenological consequences that, although at present they may seem purely academic, probably will have to be taken…
Counterfactual explanations are widely used to interpret machine learning predictions by identifying minimal changes to input features that would alter a model's decision. However, most existing counterfactual methods have not been tested…
Each new identified security threat class triggers new research and development efforts by the scientific and professional communities. In this study, we investigate the rate at which the scientific and professional communities react to new…
The advent of modern technology, permitting the measurement of thousands of characteristics simultaneously, has given rise to floods of data characterized by many large or even huge datasets. This new paradigm presents extraordinary…
Certain research strands can yield "forbidden knowledge". This term refers to knowledge that is considered too sensitive, dangerous or taboo to be produced or shared. Discourses about such publication restrictions are already entrenched in…
This article aims to show the weakness of the current scientific assessments, based on a set of contradictory pseudo-axioms. The six pseudo-axioms are deeply analysed. From the analysis are derived several conclusions. In spite of the…
Data science is not a science. It is a research paradigm with an unfathomed scope, scale, complexity, and power for knowledge discovery that is not otherwise possible and can be beyond human reasoning. It is changing our world practically…
Background: Research software plays an important role in solving real-life problems, empowering scientific innovations, and handling emergency situations. Therefore, the correctness and trustworthiness of research software are of absolute…
Cybersecurity incidents such as data breaches have become increasingly common, affecting millions of users and organizations worldwide. The complexity of cybersecurity threats challenges the effectiveness of existing security communication…