Search results for 'Modelling' (try it on Scholar)

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  1. Tarja Knuuttila (2011). Modelling and Representing: An Artefactual Approach to Model-Based Representation. Studies in History and Philosophy of Science 42 (2):262-271.score: 24.0
    The recent discussion on scientific representation has focused on models and their relationship to the real world. It has been assumed that models give us knowledge because they represent their supposed real target systems. However, here agreement among philosophers of science has tended to end as they have presented widely different views on how representation should be understood. I will argue that the traditional representational approach is too limiting as regards the epistemic value of modelling given the focus on (...)
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  2. Rosanna Keefe (2012). Modelling Vagueness: What Can We Ignore? Philosophical Studies 161 (3):453-470.score: 24.0
    A theory of vagueness gives a model of vague language and of reasoning within the language. Among the models that have been offered are Degree Theorists’ numerical models that assign values between 0 and 1 to sentences, rather than simply modelling sentences as true or false. In this paper, I ask whether we can benefit from employing a rich, well-understood numerical framework, while ignoring those aspects of it that impute a level of mathematical precision that is not present in (...)
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  3. Benedikt Löwe & Thomas Müller (2011). Data and Phenomena in Conceptual Modelling. Synthese 182 (1):131-148.score: 24.0
    The distinction between data and phenomena introduced by Bogen and Woodward (Philosophical Review 97(3):303–352, 1988) was meant to help accounting for scientific practice, especially in relation with scientific theory testing. Their article and the subsequent discussion is primarily viewed as internal to philosophy of science. We shall argue that the data/phenomena distinction can be used much more broadly in modelling processes in philosophy.
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  4. Bruce Edmonds (2000). Complexity and Scientific Modelling. Foundations of Science 5 (3):379-390.score: 24.0
    It is argued that complexity is not attributable directly to systems or processes but rather to the descriptions of their `best' models, to reflect their difficulty. Thus it is relative to the modelling language and type of difficulty. This approach to complexity is situated in a model of modelling. Such an approach makes sense of a number of aspects of scientific modelling: complexity is not situated between order and disorder; noise can be explicated by approaches to excess (...)
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  5. Brendan Clarke, Bert Leuridan & Jon Williamson (2013). Modelling Mechanisms with Causal Cycles. Synthese:1-31.score: 24.0
    Mechanistic philosophy of science views a large part of scientific activity as engaged in modelling mechanisms. While science textbooks tend to offer qualitative models of mechanisms, there is increasing demand for models from which one can draw quantitative predictions and explanations. Casini et al. (Theoria 26(1):5–33, 2011) put forward the Recursive Bayesian Networks (RBN) formalism as well suited to this end. The RBN formalism is an extension of the standard Bayesian net formalism, an extension that allows for modelling (...)
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  6. Tjerk Gauderis (2013). Modelling Abduction in Science by Means of a Modal Adaptive Logic. Foundations of Science 18 (4):611-624.score: 24.0
    Scientists confronted with multiple explanatory hypotheses as a result of their abductive inferences, generally want to reason further on the different hypotheses one by one. This paper presents a modal adaptive logic MLA s that enables us to model abduction in such a way that the different explanatory hypotheses can be derived individually. This modelling is illustrated with a case study on the different hypotheses on the origin of the Moon.
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  7. Mike Page (2000). Connectionist Modelling in Psychology: A Localist Manifesto. Behavioral and Brain Sciences 23 (4):443-467.score: 24.0
    Over the last decade, fully distributed models have become dominant in connectionist psychological modelling, whereas the virtues of localist models have been underestimated. This target article illustrates some of the benefits of localist modelling. Localist models are characterized by the presence of localist representations rather than the absence of distributed representations. A generalized localist model is proposed that exhibits many of the properties of fully distributed models. It can be applied to a number of problems that are difficult (...)
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  8. Jarmo J. Ahonen (1994). On Qualitative Modelling. AI and Society 8 (1):17-28.score: 24.0
    Fundamental assumptions behind qualitative modelling are critically considered and some inherent problems in that modelling approach are outlined. The problems outlined are due to the assumption that a sufficient set of symbols representing the fundamental features of the physical world exists. That assumption causes serious problems when modelling continuous systems. An alternative for intelligent system building for cases not suitable for qualitative modelling is proposed. The proposed alternative combines neural networks and quantitative modelling.
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  9. John Stewart & Olivier Gapenne (2004). Reciprocal Modelling of Active Perception of 2-D Forms in a Simple Tactile-Vision Substitution System. Minds and Machines 14 (3):309-330.score: 24.0
    The strategies of action employed by a human subject in order to perceive simple 2-D forms on the basis of tactile sensory feedback have been modelled by an explicit computer algorithm. The modelling process has been constrained and informed by the capacity of human subjects both to consciously describe their own strategies, and to apply explicit strategies; thus, the strategies effectively employed by the human subject have been influenced by the modelling process itself. On this basis, good qualitative (...)
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  10. Guillaume Wunsch, Michel Mouchart & Federica Russo (2014). Functions and Mechanisms in Structural-Modelling Explanations. Journal for General Philosophy of Science 45 (1):187-208.score: 24.0
    One way social scientists explain phenomena is by building structural models. These models are explanatory insofar as they manage to perform a recursive decomposition on an initial multivariate probability distribution, which can be interpreted as a mechanism. Explanations in social sciences share important aspects that have been highlighted in the mechanisms literature. Notably, spelling out the functioning the mechanism gives it explanatory power. Thus social scientists should choose the variables to include in the model on the basis of their function (...)
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  11. Han-Liang Chang (2009). Semioticians Make Strange Bedfellows! Or, Once Again: “Is Language a Primary Modelling System?”. [REVIEW] Biosemiotics 2 (2):169-179.score: 24.0
    Like other sciences, biosemiotics also has its time-honoured archive, consisting of writings by those who have been invented and revered as ancestors of the discipline. One such example is Jakob von Uexküll. As to the people who ‘invented’ him, they are either, to paraphrase a French cliché, ‘agents du cosmopolitisme sémiotique’ like Thomas Sebeok, or de jure and de facto progenitor like Thure von Uexküll. In the archive is the special issue of Semiotica 42. 1 (1982) edited by the late (...)
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  12. Zhengxin Chen (1993). From Participatory Design to Participating Problem Solving: Enhancing System Adaptability Through User Modelling. [REVIEW] AI and Society 7 (3):238-247.score: 24.0
    The issue on the role of users in knowledge-based systems can be investigated from two aspects: the design aspect and the functionality aspect. Participatory design is an important approach for the first aspect while system adaptability supported by user modelling is crucial to the second aspect. In the article, we discuss the second aspect. We view a knowledge-based computer system as the partner of users' problem-solving process, and we argue that the system functionality can be enhanced by adapting the (...)
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  13. John Kingston, Burkhard Schafer & Wim Vandenberghe (2004). Towards a Financial Fraud Ontology: A Legal Modelling Approach. [REVIEW] Artificial Intelligence and Law 12 (4):419-446.score: 22.0
    This document discusses the status of research on detection and prevention of financial fraud undertaken as part of the IST European Commission funded FF POIROT (Financial Fraud Prevention Oriented Information Resources Using Ontology Technology) project. A first task has been the specification of the user requirements that define the functionality of the financial fraud ontology to be designed by the FF POIROT partners. It is claimed here that modeling fraudulent activity involves a mixture of law and facts as well as (...)
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  14. Dave Billinge & Tom Addis (2008). Seeking Allies: Modelling How Listeners Choose Their Musical Friends. [REVIEW] Foundations of Science 13 (1):53-66.score: 22.0
    In this paper we describe in some detail a formal computer model of inferential discourse based on a belief system. The key issue is that a logical model in a computer, based on rational sets, can usefully model a human situation based on irrational sets. The background of this work is explained elsewhere, as is the issue of rational and irrational sets (Billinge and Addis, in: Magnani and Dossena (eds.), Computing, philosophy and cognition, 2004; Stepney et al., Journey: Non-classical philosophy—socially (...)
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  15. Michael E. Brown & Linda K. Treviño (2013). Do Role Models Matter? An Investigation of Role Modeling as an Antecedent of Perceived Ethical Leadership. Journal of Business Ethics:1-12.score: 22.0
    Thus far, we know much more about the significant outcomes of perceived ethical leadership than we do about its antecedents. In this study, we focus on multiple types of ethical role models as antecedents of perceived ethical leadership. According to social learning theory, role models facilitate the acquisition of moral and other types of behavior. Yet, we do not know whether having had ethical role models influences follower perceptions of one’s ethical leadership and, if so, what kinds of role models (...)
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  16. Jacinto González-Pachón & Sixto Ríos-Insua (1999). Mixture of Maximal Quasi Orders: A New Approach to Preference Modelling. Theory and Decision 47 (1):73-88.score: 22.0
    Normative theories suggest that inconsistencies be pointed out to the Decision Maker who is thus given the chance to modify his/her judgments. In this paper, we suggest that the inconsistencies problem be transferred from the Decision Maker to the Analyst. With the Mixture of Maximal Quasi Orders, rather than pointing out incoherences for the Decision Maker to change, these inconsistencies may be used as new source of information to model his/her preferences.
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  17. Guido Boella, Dov M. Gabbay, Leendert van der Torre & Serena Villata (2009). Meta-Argumentation Modelling I: Methodology and Techniques. [REVIEW] Studia Logica 93 (2-3):297-355.score: 22.0
    In this paper, we introduce the methodology and techniques of meta-argumentation to model argumentation. The methodology of meta-argumentation instantiates Dung’s abstract argumentation theory with an extended argumentation theory, and is thus based on a combination of the methodology of instantiating abstract arguments, and the methodology of extending Dung’s basic argumentation frameworks with other relations among abstract arguments. The technique of meta-argumentation applies Dung’s theory of abstract argumentation to itself, by instantiating Dung’s abstract arguments with meta-arguments using a technique called flattening. (...)
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  18. Yves Maury, Morgane Gauthier, Marc Peschanski & Cécile Martinat (2012). Human Pluripotent Stem Cells for Disease Modelling and Drug Screening. Bioessays 34 (1):61-71.score: 21.0
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  19. Irmeli Luukkonen and Juha Mykkänen (2012). Analyzing Process Modelling as Work Activity. Iris 35.score: 21.0
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  20. Halfdan Petursson, Linn Getz, Johann A. Sigurdsson & Irene Hetlevik (2009). Can Individuals with a Significant Risk for Cardiovascular Disease Be Adequately Identified by Combination of Several Risk Factors? Modelling Study Based on the Norwegian HUNT 2 Population. Journal of Evaluation in Clinical Practice 15 (1):103-109.score: 21.0
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  21. Oz Pomp & Alan Colman (2013). Disease Modelling Using Induced Pluripotent Stem Cells: Status and Prospects. Bioessays 35 (3):271-280.score: 21.0
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  22. Anna Conte & Peter G. Moffatt (2014). The Econometric Modelling of Social Preferences. Theory and Decision 76 (1):119-145.score: 21.0
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  23. H. J. Nock & S. J. Young (2002). Modelling Asynchrony in Automatic Speech Recognition Using Loosely Coupled Hidden Markov Models. Cognitive Science 26 (3):283-301.score: 21.0
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  24. Adam Toon (2010). The Ontology of Theoretical Modelling: Models as Make-Believe. Synthese 172 (2):301-315.score: 20.0
    The descriptions and theoretical laws scientists write down when they model a system are often false of any real system. And yet we commonly talk as if there were objects that satisfy the scientists’ assumptions and as if we may learn about their properties. Many attempt to make sense of this by taking the scientists’ descriptions and theoretical laws to define abstract or fictional entities. In this paper, I propose an alternative account of theoretical modelling that draws upon Kendall (...)
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  25. Nick Braisby (1998). Compositionality and the Modelling of Complex Concepts. Minds and Machines 8 (4):479-508.score: 20.0
    The nature of complex concepts has important implications for the computational modelling of the mind, as well as for the cognitive science of concepts. This paper outlines the way in which RVC – a Relational View of Concepts – accommodates a range of complex concepts, cases which have been argued to be non-compositional. RVC attempts to integrate a number of psychological, linguistic and psycholinguistic considerations with the situation-theoretic view that information-carrying relations hold only relative to background situations. The central (...)
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  26. Samuel Ruhmkorff (2007). The Descriptive Criterion and Models of God-Modeling: Response to Hustwit's “Can Models of God Compete?”. Philosophia 35 (3-4):441-444.score: 20.0
    In “Can Models of God Compete?”, J. R. Hustwit engages with fundamental questions regarding the epistemological foundations of modeling God. He argues that the approach of fallibilism best captures the criteria he employs to choose among different “models of God-modeling,” including one criterion that I call the Descriptive Criterion. I argue that Hustwit’s case for fallibilism should include both a stronger defense for the Descriptive Criterion and an explanation of the reasons that fallibilism does not run awry of this criterion (...)
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  27. Francesco Amigoni & Viola Schiaffonati (2008). A Multiagent Approach to Modelling Complex Phenomena. Foundations of Science 13 (2):113-125.score: 20.0
    Designing models of complex phenomena is a difficult task in engineering that can be tackled by composing a number of partial models to produce a global model of the phenomena. We propose to embed the partial models in software agents and to implement their composition as a cooperative negotiation between the agents. The resulting multiagent system provides a global model of a phenomenon. We applied this approach in modelling two complex physiological processes: the heart rate regulation and the glucose-insulin (...)
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  28. D. M. Bailer-Jones (1999). Creative Strategies Employed in Modelling: A Case Study. [REVIEW] Foundations of Science 4 (4):375-388.score: 20.0
    This paper examines creative strategies employed inscientific modelling. It is argued that being creativepresents not a discrete event, but rather an ongoingeffort consisting of many individual `creative acts''.These take place over extended periods of time andcan be carried out by different people, working ondifferent aspects of the same project. The example ofextended extragalactic radio sources shows that, inorder to model a complicated phenomenon in itsentirety, the modelling task is split up into smallerproblems that result in several sub-models. This (...)
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  29. Jordi Cat (2005). Modeling Cracks and Cracking Models: Structures, Mechanisms, Boundary Conditions, Constraints, Inconsistencies and the Proper Domains of Natural Laws. Synthese 146 (3):447 - 487.score: 18.0
    The emphasis on models hasn’t completely eliminated laws from scientific discourse and philosophical discussion. Instead, I want to argue that much of physics lies beyond the strict domain of laws. I shall argue that in important cases the physics, or physical understanding, does not lie either in laws or in their properties, such as universality, consistency and symmetry. I shall argue that the domain of application commonly attributed to laws is too narrow. That is, laws can still play an important, (...)
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  30. Rosária S. Justi & John K. Gilbert (2002). Philosophy of Chemistry in University Chemical Education: The Case of Models and Modelling. [REVIEW] Foundations of Chemistry 4 (3):213-240.score: 18.0
    If chemistry is to be taught successfully, teachers must have a good subject matter knowledge (SK) of the ideas with which they are dealing, the nature of this falling within the orbit of philosophy of chemistry. They must also have a good pedagogic content knowledge (PCK), the ability to communicate SK to students, the nature of this falling within the philosophy and psychology of chemical education. Taking the case of models and modelling, important themes in the philosophy of chemistry, (...)
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  31. James R. Griesemer (1990). Modeling in the Museum: On the Role of Remnant Models in the Work of Joseph Grinnell. [REVIEW] Biology and Philosophy 5 (1):3-36.score: 18.0
    Accounts of the relation between theories and models in biology concentrate on mathematical models. In this paper I consider the dual role of models as representations of natural systems and as a material basis for theorizing. In order to explicate the dual role, I develop the concept of a remnant model, a material entity made from parts of the natural system(s) under study. I present a case study of an important but neglected naturalist, Joseph Grinnell, to illustrate the extent to (...)
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  32. D. C. Gooding & T. R. Addis (2008). Modelling Experiments as Mediating Models. Foundations of Science 13 (1):17-35.score: 18.0
    Syntactic and structural models specify relationships between their constituents but cannot show what outcomes their interaction would produce over time in the world. Simulation consists in iterating the states of a model, so as to produce behaviour over a period of simulated time. Iteration enables us to trace the implications and outcomes of inference rules and other assumptions implemented in the models that make up a theory. We apply this method to experiments which we treat as models of the particular (...)
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  33. Björn Kralemann & Claas Lattmann (2013). Models as Icons: Modeling Models in the Semiotic Framework of Peirce's Theory of Signs. Synthese 190 (16):3397-3420.score: 18.0
    In this paper, we try to shed light on the ontological puzzle pertaining to models and to contribute to a better understanding of what models are. Our suggestion is that models should be regarded as a specific kind of signs according to the sign theory put forward by Charles S. Peirce, and, more precisely, as icons, i.e. as signs which are characterized by a similarity relation between sign (model) and object (original). We argue for this (1) by analyzing from a (...)
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  34. Michael Thomas & Annette Karmiloff-Smith (2002). Are Developmental Disorders Like Cases of Adult Brain Damage? Implications From Connectionist Modelling. Behavioral and Brain Sciences 25 (6):727-750.score: 18.0
    It is often assumed that similar domain-specific behavioural impairments found in cases of adult brain damage and developmental disorders correspond to similar underlying causes, and can serve as convergent evidence for the modular structure of the normal adult cognitive system. We argue that this correspondence is contingent on an unsupported assumption that atypical development can produce selective deficits while the rest of the system develops normally (Residual Normality), and that this assumption tends to bias data collection in the field. Based (...)
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  35. Oana Apostol & Salme Näsi (2010). Institutional Implications for Stakeholder Modelling: Looking at Institutions in a Centralised Economy. [REVIEW] Journal of Business Ethics 96 (S1):33-38.score: 18.0
    Originating in the Anglo-American management literature, stakeholder thinking embraces a set of common reasoning and rests on a range of assumptions that pay little attention to the institutional variations across countries and regions with different economic systems. Our aim in this article is to contribute to the stakeholder literature by discussing the significance and implications of this institutional diversity for the stakeholder model.
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  36. Mathias Frisch (2013). Modeling Climate Policies: A Critical Look at Integrated Assessment Models. Philosophy and Technology 26 (2):117-137.score: 18.0
    Climate change presents us with a problem of intergenerational justice. While any costs associated with climate change mitigation measures will have to be borne by the world’s present generation, the main beneficiaries of mitigation measures will be future generations. This raises the question to what extent present generations have a responsibility to shoulder these costs. One influential approach for addressing this question is to appeal to neo-classical economic cost–benefit analyses and so-called economy-climate “integrated assessment models” to determine what course of (...)
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  37. A. Defontaine, A. Hernández & G. Carrault (2004). Multi-Formalism Modelling and Simulation: Application to Cardiac Modelling. Acta Biotheoretica 52 (4).score: 18.0
    Cardiovascular modelling has been a major research subject for the last decade. Different cardiac models have been developed at a cellular level as well as at the whole organ level. Most of these models are defined by a comprehensive cellular modelling using continuous formalisms or by a tissue-level modelling often based on discrete formalisms. Nevertheless, both views still suffer from difficulties that reduce their clinical applications: the first approach requires heavy computational resources while the second one is (...)
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  38. Uwe Meixner (2010). Modelling Metaphysics: The Metaphysics of a Model. Ontos.score: 18.0
    This book models and simulates metaphysics by presenting the metaphysics of a model.
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  39. Guglielmo Tamburrini & Edoardo Datteri (2005). Machine Experiments and Theoretical Modelling: From Cybernetic Methodology to Neuro-Robotics. [REVIEW] Minds and Machines 15 (3-4):335-358.score: 18.0
    Cybernetics promoted machine-supported investigations of adaptive sensorimotor behaviours observed in biological systems. This methodological approach receives renewed attention in contemporary robotics, cognitive ethology, and the cognitive neurosciences. Its distinctive features concern machine experiments, and their role in testing behavioural models and explanations flowing from them. Cybernetic explanations of behavioural events, regularities, and capacities rely on multiply realizable mechanism schemata, and strike a sensible balance between causal and unifying constraints. The multiple realizability of cybernetic mechanism schemata paves the way to principled (...)
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  40. Trevor J. M. Bench-Capon (2003). Try to See It My Way: Modelling Persuasion in Legal Discourse. [REVIEW] Artificial Intelligence and Law 11 (4):271-287.score: 18.0
    In this paper I argue that to explain and resolve some kinds of disagreement we need to go beyond what logic alone can provide. In particular, following Perelman, I argue that we need to consider how arguments are ascribed different strengths by different audiences, according to how accepting these arguments promotes values favoured by the audience to which they are addressed. I show how we can extend the standard framework for modelling argumentation systems to allow different audiences to be (...)
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  41. Jean-Pierre Gourret (1995). Modelling the Mitotic Apparatus. Acta Biotheoretica 43 (1-2).score: 18.0
    This bibliographical review of the modelling of the mitotic apparatus covers a period of one hundred and twenty years, from the discovery of the bipolar mitotic spindle up to the present day. Without attempting to be fully comprehensive, it will describe the evolution of the main ideas that have left their mark on a century of experimental and theoretical research. Fol and Bütschli's first writings date back to 1873, at a time when Schleiden and Schwann's cell theory was rapidly (...)
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  42. Kenneth A. Taylor (2001). Applying Continuous Modelling to Consciousness. Journal of Consciousness Studies 8 (2):45-60.score: 17.0
  43. Fabian Neuhaus & Barry Smith (2008). Modelling Principles and Methodologies: Relations in Anatomical Ontologies. In Albert Burger, Duncan Davidson & Richard Baldock (eds.), Anatomy Ontologies for Bioinformatics: Principles and Practice. Springer.score: 17.0
    It is now increasingly accepted that many existing biological and medical ontologies can be improved by adopting tools and methods that bring a greater degree of logical and ontological rigor. In this chapter we will focus on the merits of a logically sound approach to ontologies from a methodological point of view. As we shall see, one crucial feature of a logically sound approach is that we have clear and functional definitions of the relational expressions such as ‘is a’ and (...)
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  44. Tina Balke, Marina De Vos & Julian Padget (2013). I-ABM: Combining Institutional Frameworks and Agent-Based Modelling for the Design of Enforcement Policies. Artificial Intelligence and Law 21 (4):371-398.score: 17.0
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  45. [deleted]Tyler D. Bancroft, William E. Hockley & Philip Servos (2011). Vibrotactile Working Memory as a Model Paradigm for Psychology, Neuroscience, and Computational Modeling. Frontiers in Human Neuroscience 5.score: 17.0
  46. Jung‐Chen Chang, Tony H.‐H. Chen, Stephen W. Duffy, Amy M.‐F. Yen & Sam L.‐S. Chen (2010). Decision Modelling of Economic Evaluation of Intervention Programme of Breast Cancer. Journal of Evaluation in Clinical Practice 16 (6):1282-1288.score: 17.0
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  47. Dario Gregori, Lara Lusa, Rosalba Rosato & Luciano Silvestri (2008). Evaluating Effectiveness of Preoperative Testing Procedure: Some Notes on Modelling Strategies in Multi‐Centre Surveys. Journal of Evaluation in Clinical Practice 14 (1):11-18.score: 17.0
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  48. Dario Gregori, Rosalba Rosato, Massimo Zecchin, Ileana Baldi & Andrea Di Lenarda (2008). Heart Failure and Sudden Death in Dilated Cardiomyopathy: A Hidden Competition We Should Not Forget About When Modelling Mortality. Journal of Evaluation in Clinical Practice 14 (1):53-58.score: 17.0
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  49. John L. Moran, Andrew D. Bersten, Patricia J. Solomon, Cyrus Edibam & Tamara Hunt (2008). Modelling Survival in Acute Severe Illness: Cox Versus Accelerated Failure Time Models. Journal of Evaluation in Clinical Practice 14 (1):83-93.score: 17.0
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  50. Waldemar Skrzypczak (2006). Analog-Based Modelling of Meaning Representations in English. Nicolaus Copernicus University Press.score: 17.0
     
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