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Measuring inconsistency is viewed as an important issue related to handling inconsistencies. Good measures are supposed to satisfy a set of rational properties. However, defining sound properties is sometimes problematic. In this paper, we…

Artificial Intelligence · Computer Science 2014-06-03 Said Jabbour , Yue Ma , Badran Raddaoui , Lakhdar Sais , Yakoub Salhi

Better representation of the uncertainty in a data visualisation is a focus of recent research activity. A problem with the current literature is that there is a lack of clarity about the definition of uncertainty and what it means to…

Human-Computer Interaction · Computer Science 2026-03-30 Harriet Mason , Dianne Cook , Sarah Goodwin , Emi Tanaka , Susan VanderPlas

Many measurements at collider experiments study physics candidates that are a subset of a collision event. The presence of multiple such candidates in a given event can cause raw biases which are large compared to typical statistical…

High Energy Physics - Experiment · Physics 2019-08-22 Patrick Koppenburg

No consensus seems to exist as to what constitutes a measurement which is still considered somewhat mysterious in many respects in quantum mechanics. At successive stages mathematical theory of measure, metrology and measurement theory…

Quantum Physics · Physics 2008-11-21 Paolo Rocchi , Orlando Panella

The study of the brain's representations of uncertainty is a central topic in neuroscience. Unlike most quantities of which the neural representation is studied, uncertainty is a property of an observer's beliefs about the world, which…

Neurons and Cognition · Quantitative Biology 2023-10-12 Edgar Y Walker , Stephan Pohl , Rachel N Denison , David L Barack , Jennifer Lee , Ned Block , Wei Ji Ma , Florent Meyniel

Uncertainty estimation is critical for deploying reasoning language models, yet remains poorly understood under extended chain-of-thought reasoning. We study parallel sampling as a fully black-box approach using verbalized confidence and…

Artificial Intelligence · Computer Science 2026-03-20 Maksym Del , Markus Kängsepp , Marharyta Domnich , Ardi Tampuu , Lisa Yankovskaya , Meelis Kull , Mark Fishel

We present an online and data-driven uncertainty quantification method to enable the development of safe human-robot collaboration applications. Safety and risk assessment of systems are strongly correlated with the accuracy of…

Robotics · Computer Science 2022-09-02 Woo-Jeong Baek , Christoph Ledermann , Torsten Kröger

Adequate uncertainty representation and quantification have become imperative in various scientific disciplines, especially in machine learning and artificial intelligence. As an alternative to representing uncertainty via one single…

Machine Learning · Computer Science 2023-06-19 Yusuf Sale , Michele Caprio , Eyke Hüllermeier

Science is an inherently quantitative endeavor, and general education science courses are taken by a majority of college students. As such, they are a powerful venue for advancing students' skills and attitudes toward mathematics. This…

Physics Education · Physics 2015-07-16 Katherine B. Follette , Donald W. McCarthy , Erin Dokter , Sanlyn Buxner , Edward Prather

Quantum uncertainty is described here in two guises: indeterminacy with its concomitant indeterminism of measurement outcomes, and fuzziness, or unsharpness. Both features were long seen as obstructions of experimental possibilities that…

Quantum Physics · Physics 2011-01-04 Paul Busch

Standard methods, standard test conditions and the use of good sensory practices are key elements of sensory testing. However, while compliance assessment by trained and expert assessors is well developed, few information is available on…

Applications · Statistics 2025-02-07 László Sipos , Kolos Csaba Ágoston , Péter Biró , Sándor Bozóki , László Csató

When you measure an observable, A, in Quantum Mechanics, the state of the system changes. This, in turn, affects the quantum-mechanical uncertainty in some non-commuting observable, B. The standard Uncertainty Relation puts a lower bound on…

Quantum Physics · Physics 2015-06-12 Jacques Distler , Sonia Paban

Uncertainty Sampling is an Active Learning strategy that aims to improve the data efficiency of machine learning models by iteratively acquiring labels of data points with the highest uncertainty. While it has proven effective for…

Machine Learning · Computer Science 2025-02-28 Dominik Fuchsgruber , Tom Wollschläger , Bertrand Charpentier , Antonio Oroz , Stephan Günnemann

When a measurement of a physical quantity is reported, the total uncertainty is usually decomposed into statistical and systematic uncertainties. This decomposition is not only useful to understand the contributions to the total…

Data Analysis, Statistics and Probability · Physics 2024-03-18 Andrés Pinto , Zhibo Wu , Fabrice Balli , Nicolas Berger , Maarten Boonekamp , Émilien Chapon , Tatsuo Kawamoto , Bogdan Malaescu

We discuss the development of a research-based conceptual multiple-choice survey related to magnetism. We also discuss the use of the survey to investigate gender differences in students' difficulties with concepts related to magnetism. We…

Physics Education · Physics 2016-02-17 Jing Li , Chandralekha Singh

Measurement is an integral part of modern science, providing the fundamental means for evaluation, comparison, and prediction. In the context of visualization, several different types of measures have been proposed, ranging from approaches…

Graphics · Computer Science 2019-09-13 Fabian Bolte , Stefan Bruckner

Measurement professionals cannot come to an agreement on the definition of the term 'item fairness'. In this paper a continuous measure of item unfairness is proposed. The more the unfairness measure deviates from zero, the less fair the…

Artificial Intelligence · Computer Science 2020-10-06 Yefim Bakman

Measurement outcomes of a quantum state can be genuinely random (unpredictable) according to the basic laws of quantum mechanics. The Heisenberg-Robertson uncertainty relation puts constrains on the accuracy of two noncommuting observables.…

Quantum Physics · Physics 2017-09-13 Xiao Yuan , Ge Bai , Tianyi Peng , Xiongfeng Ma

In this companion paper, we explore the use of isomorphic problem pairs (IPPs) to assess introductory physics students' ability to solve and successfully transfer problem-solving knowledge from one context to another in mechanics. We call…

Physics Education · Physics 2016-02-25 Chandralekha Singh

Research-based multiple-choice questions implemented in class with peer instruction have been shown to be an effective tool for improving students' engagement and learning outcomes. Moreover, multiple-choice questions that are carefully…

Physics Education · Physics 2025-02-11 Yangqiuting Li , Chandralekha Singh
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