23 papers · ranked by Valyu relevance
Ken Gu, Eunice Jun, Tim Althoff
Figure 1: Overview of Multiverse Analysis. In traditional analyses, an analyst may consider multiple decisions in their analysis data filter cutoff, statistical modeling approach (e.g., frequentist, Bayesian), and Bayesian family function (e.g., binomial, lognormal). Traditionally, analysts may conduct multiple…
Shiyang Liu
Understanding the challenges inherent in Chinese-Spanish sight translation for undergraduate students is essential for enhancing their interpretation ability and accuracy. However, sight translation errors have rarely been studied, especially for Chinese-Spanish language pair. This study builds a corpus of Chinese…
Gabrielle Gauthier-melancon, Orlando Marquez Ayala, Lindsay D. Brin, Christopher J. Tyler + 4 more
'Christopher J. Tyler' 'Frédéric Branchaud-Charron' 'Joseph Marinier' 'Karine Grande' 'Di Le'] We present Azimuth, an open-source and easyto-use tool to perform error analysis for text classification. Compared to other stages of the ML development cycle, such as model training and hyper-parameter tuning, the process…
Yajin Zhuang, Liwen Chen, Wei Lun Wong
Errors, as linguistic manifestations of cognitive challenges in interpreting, have attracted considerable attention in the fields of teaching, practice, and assessment. This paper examines the nature of interpreting errors among Chinese EFL (English as a Foreign Language) learners and explores their relationship with…
Zhenhua Luo, Xinyuan Yang, Yong Zhang, Bin Xiong + 1 more
This study explored individual differences among senior high school students in detecting and correcting logical errors in mathematical reasoning. Eight participants with high and average mathematical abilities each were recruited from a key high school in Shanghai to solve three error-detecting tasks by thinking…
Tyler J Adkins, Han Zhang, Taraz G Lee
Humans tend to slow down after making an error. A longstanding account of this post-error slowing is that people are simply more cautious. However, accuracy typically does not improve following an error leading some researchers to suggest that an initial ‘orienting’ response may initially impair performance immediately…
Authors not listed
Bayesian optimization (BO) has become increasingly important for experimental optimization across scientific domains, yet implementing BO pipelines requires significant programming expertise and familiarity with specialized frameworks. This creates a barrier for domain experts who could benefit from BO but lack the…
Atsushi Shirafuji, Taku Matsumoto, Md Faizul Ibne Amin, Yutaka Watanobe
'Yutaka Watanobe'] Abstract—Finding and fixing errors is a time-consuming task not only for novice programmers but also for expert programmers. Prior work has identified frequent error patterns among various levels of programmers. However, the differences in the tendencies between novices and experts have yet to be…
Authors not listed
Moving bed reactors (MBRs) are widely used in various industrial processes, making the development of mathematical models crucial for their design, optimization, and control. This study presents a semi-analytical solution (SAS) for a lumped parameter kinetic and heat transfer model of a tubular MBR, where a first-order…
Eva Niessen, Jonas Wickert, Martin Schober, Gereon R. Fink + 2 more
Influential theories on error processing assume that when we conduct errors adaptive processes are triggered to improve our behaviour and prevent errors in the future. These processes appear to be more effective after participants have detected an error. Therefore, the assessment of error awareness allowing a…
Ulrich Knief, Wolfgang Forstmeier
When multiple studies on the same research question, or multiple analyses of the same dataset are summarized in a meta-analysis, our confidence intervals (CIs) are put to a relentless test of reliability. While we might hope that 95% of the CIs would contain the meta-analytic mean value (and therefore presumably also…
Gezelle Dali, Méadhbh Brosnan, Jeggan Tiego, Beth P. Johnson + 3 more
Goal-directed behaviour is dependent upon the ability to detect errors and implement appropriate post-error adjustments. Accordingly, several studies have explored the neural activity underlying error-monitoring processes, identifying the insula cortex as crucial for error awareness and reporting mixed findings with…
Daniel Kadlec, Kristin L. Sainani, Sophia Nimphius
Background and Objective Meta-analysis and meta-regression are often highly cited and may influence practice. Unfortunately, statistical errors in meta-analyses are widespread and can lead to flawed conclusions. The purpose of this article was to review common statistical errors in meta-analyses and to document their…
Simon Iveson, Kevin Galvin
This paper presents a simple relationship for estimating the uncertainty in the overall yield and species recovery when the two-product formula is applied to assays of the feed, product and tailings streams of a steady-state mineral separator. The non-linearity of the two-product formula means the reliability of these…
Maria H. Rasmussen, Chenru Duan, Heather J. Kulik, Jan Halborg Jensen
With the increasingly more important role of machine learning (ML) models in chemical research, the need for putting a level of confidence to the model predictions naturally arises. Several methods for obtaining uncertainty estimates have been proposed in recent years but consensus on the evaluation of these have yet…
Zhenyu Xu, Kun Zhang, Victor S. Sheng
Pseudocode and Graph Neural Networks Authors: ['Zhenyu Xu' 'Kun Zhang' 'Victor S. Sheng'] Abstract. Pseudocode is extensively used in introductory programming courses to instruct computer science students in algorithm design, utilizing natural language to define algorithmic behaviors. This learning approach enables…
Han Cui, Menglei Xie, Ting Wei Su, Chengyu Zhang + 1 more
Analyzers From the Perspective of Historical Issues Authors: ['Han Cui' 'Menglei Xie' 'Ting Wei Su' 'Chengyu Zhang' 'Shin Hwei Tan'] Static code analyzers are widely used to help find program flaws. However, in practice the effectiveness and usability of such analyzers is affected by the problems of false negatives…
Authors not listed
This study presents a validation and refinement of the “yellow cards” error detection workflow that can be applied to any property connected to molecular structure. In our implementation the workflow employed 5 predictive models with each assigning a “yellow card” to 5% of the entries with worst prediction accuracy.…
Sara-Jane Lécuyer, Keleiali'i Urima, Carole Sénéchal, Frank Crispino
This exploratory research examines the implication of science in 92 Canadian wrongful convictions officially recognized by the state. The analysis revealed that science played a role in 30 cases, but 97% of those errors stemmed from the misinterpretation or overstatement of reliable scientific results, predominantly in…
H. Sherry Zhang, Roger D. Peng
Checks Authors: ['H. Sherry Zhang' 'Roger D. Peng'] In data analysis, unexpected results often prompt researchers to revisit their procedures to identify potential issues. While some researchers may struggle to identify the root causes, experienced researchers can often quickly diagnose problems by checking a few key…
Surajit Nandi, Jonas Busk, Peter Bjørn Jørgensen, Tejs Vegge + 1 more
Workflows to predict chemical reaction networks based on density functional theory (DFT) are prone to systematic errors in reaction energy due to the extensive use of cheap DFT exchange-correlation functionals to limit computational cost. Recently, machine learning-based models are increasingly applied to mitigate this…
Hariom Dhungana
In maintenance engineering, effective decision-making is critical to ensuring system reliability and operational efficiency. Modern industrial systems are monitored by a multitude of sensors that generate large volumes of data. However, traditional condition monitoring techniques face several limitations: they rely…
Max Neuwinger, Dirk Riehle
—The design of effective programming languages, libraries, frameworks, tools, and platforms for data engineering strongly depends on their ease and correctness of use. Anyone who ignores that it is humans who use these tools risks building tools that are useless, or worse, harmful. To ensure our data engineering tools…