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As algorithmic decision-making systems become more prevalent in society, ensuring the fairness of these systems is becoming increasingly important. Whilst there has been substantial research in building fair algorithmic decision-making…
Observational studies are a key resource for causal inference but are often affected by systematic biases. Prior work has focused mainly on detecting these biases, via sensitivity analyses and comparisons with randomized controlled trials,…
The claim that there is an inconsistency of quantum-classical dynamics [1] is investigated. We point out that a consistent formulation of quantum and classical dynamics which can be used to describe quantum measurement processes is already…
Evaluation of journals for quality is one of the dominant themes of bibliometrics since journals are the primary venue of vetting and distribution of scholarship. There are many criticisms of quantifying journal impact with bibliometrics…
Machine learning is now ubiquitous in societal decision-making, for example in evaluating job candidates or loan applications, and it is increasingly important to take into account how classified agents will react to the learning…
As a quantification of the main bottleneck to flow over a graph, the network property of conductance plays an important role in the process of synchronization of network-coupled dynamical systems. Diffusive coupling terms serve not only to…
Sequence classification is the supervised learning task of building models that predict class labels of unseen sequences of symbols. Although accuracy is paramount, in certain scenarios interpretability is a must. Unfortunately, such…
This short paper introduces the u-index, a simple and objective metric to evaluate the impact and relevance of academic research output, as a possible alternative to widespread metrics such as the h-index or the i10-index. The proposed…
The ongoing paradigm change in the scholarly publication system ('science is turning to e-science') makes it necessary to construct alternative evaluation criteria/metrics which appropriately take into account the unique characteristics of…
Machine prediction algorithms (e.g., binary classifiers) often are adopted on the basis of claimed performance using classic metrics such as sensitivity and predictive value. However, classifier performance depends heavily upon the context…
A new percentile-based rating scale P100 has recently been proposed to describe the citation impact in terms of the distribution of the unique citation values. Here I investigate P100 for 5 example datasets, two simple fictitious models and…
Kendall rank correlation coefficient is used to measure the ordinal association between two measurements. In this paper, we introduce the Concordance coefficient as a generalization of the Kendall rank correlation, and illustrate its use to…
Journal rankings are widely used and are often based on citation data in combination with a network perspective. We argue that some of these network-based rankings can produce misleading results. From a theoretical point of view, we show…
Citation and publication profiles are gaining importance for the evaluation of top researchers when it comes to the appropriation of funding for excellence programs or career promotion judgments. Indicators like the Normalized Mean Citation…
It is shown that under certain circumstances in particular for small datasets the recently proposed citation impact indicators I3(6PR) and R(6,k) behave inconsistently when additional papers or citations are taken into consideration. Three…
The predictive power of the h-index has been shown to depend for a long time on citations to rather old publications. This has raised doubts about its usefulness for predicting future scientific achievements. Here I investigate a variant…
Transformers demonstrate impressive performance on a range of reasoning benchmarks. To evaluate the degree to which these abilities are a result of actual reasoning, existing work has focused on developing sophisticated benchmarks for…
In research policy, effective measures that lead to improvements in the generation of knowledge must be based on reliable methods of research assessment, but for many countries and institutions this is not the case. Publication and citation…
Properties of a percentile-based rating scale needed in bibliometrics are formulated. Based on these properties, P100 was recently introduced as a new citation-rank approach (Bornmann, Leydesdorff, & Wang, in press). In this paper, we…
The link prediction task on knowledge graphs without explicit negative triples in the training data motivates the usage of rank-based metrics. Here, we review existing rank-based metrics and propose desiderata for improved metrics to…