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

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  1. Nicholas Shea (2012). Reward Prediction Error Signals Are Meta‐Representational. Noûs 48 (2):314-341.
    1. Introduction 2. Reward-Guided Decision Making 3. Content in the Model 4. How to Deflate a Metarepresentational Reading Proust and Carruthers on metacognitive feelings 5. A Deflationary Treatment of RPEs? 5.1 Dispensing with prediction errors 5.2 What is use of the RPE focused on? 5.3 Alternative explanations—worldly correlates 5.4 Contrast cases 6. Conclusion Appendix: Temporal Difference Learning Algorithms.
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  2.  32
    Michele Ginammi (2016). Avoiding Reification: Heuristic Effectiveness of Mathematics and the Prediction of the Omega Minus Particle. Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 53:20-27.
    According to Steiner (1998), in contemporary physics new important discoveries are often obtained by means of strategies which rely on purely formal mathematical considerations. In such discoveries, mathematics seems to have a peculiar and controversial role, which apparently cannot be accounted for by means of standard methodological criteria. M. Gell-Mann and Y. Ne׳eman׳s prediction of the Ω− particle is usually considered a typical example of application of this kind of strategy. According to Bangu (2008), this prediction is apparently (...)
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  3. Jakob Hohwy (forthcoming). Prediction Error Minimization, Mental and Developmental Disorder, and Statistical Theories of Consciousness. In Rocco Gennaro (ed.), Disturbed Consciousness: New Essays on Psychopathology and Theories of Consciousness. MIT Press
    This chapter seeks to recover an approach to consciousness from a general theory of brain function, namely the prediction error minimization theory. The way this theory applies to mental and developmental disorder demonstrates its relevance to consciousness. The resulting view is discussed in relation to a contemporary theory of consciousness, namely the idea that conscious perception depends on Bayesian metacognition; this theory is also supported by considerations of psychopathology. This Bayesian theory is first disconnected from the higher-order thought theory, (...)
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  4.  54
    Simon Blackburn (1973). Reason and Prediction. London,Cambridge University Press.
    An original study of the philosophical problems associated with inductive reasoning. Like most of the main questions in epistemology, the classical problem of induction arises from doubts about a mode of inference used to justify some of our most familiar and pervasive beliefs. The experience of each individual is limited and fragmentary, yet the scope of our beliefs is much wider; and it is the relation between belief and experience, in particular the belief that the future will in some respects (...)
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  5. Lincoln Colling, William Thompson & John Sutton (2013). Motor Experience Interacts with Effector Information During Action Prediction. Proceedings of the 35th Annual Conference of the Cognitive Science Society:2082-2087.
    Recent theory suggests that action prediction relies of a motor emulation mechanism that works by mapping observed actions onto the observer action system so that predictions can be generated using that same predictive mechanisms that underlie action control. This suggests that action prediction may be more accurate when there is a more direct mapping between the stimulus and the observer. We tested this hypothesis by comparing prediction accuracy for two stimulus types. A mannequin stimulus which contained information (...)
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  6.  26
    Gregor Betz (2015). Are Climate Models Credible Worlds? Prospects and Limitations of Possibilistic Climate Prediction. European Journal for Philosophy of Science 5 (2):191-215.
    Climate models don’t give us probabilistic forecasts. To interpret their results, alternatively, as serious possibilities seems problematic inasmuch as climate models rely on contrary-to-fact assumptions: why should we consider their implications as possible if their assumptions are known to be false? The paper explores a way to address this possibilistic challenge. It introduces the concepts of a perfect and of an imperfect credible world, and discusses whether climate models can be interpreted as imperfect credible worlds. That would allow one to (...)
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  7. Roberto Festa (2007). Verisimilitude, Cross Classification and Prediction Logic. Approaching the Statistical Truth by Falsified Qualitative Theories. Mind and Society 6 (1):91-114.
    In this paper it is argued that qualitative theories (Q-theories) can be used to describe the statistical structure of cross classified populations and that the notion of verisimilitude provides an appropriate tool for measuring the statistical adequacy of Q-theories. First of all, a short outline of the post-Popperian approaches to verisimilitude and of the related verisimilitudinarian non-falsificationist methodologies (VNF-methodologies) is given. Secondly, the notion of Q-theory is explicated, and the qualitative verisimilitude of Q-theories is defined. Afterwards, appropriate measures for the (...)
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  8.  18
    C. D. McCoy (forthcoming). Prediction in General Relativity. Synthese:1-19.
    Several authors have claimed that prediction is essentially impossible in the general theory of relativity, the case being particularly strong, it is said, when one fully considers the epistemic predicament of the observer. Each of these claims rests on the support of an underdetermination argument and a particular interpretation of the concept of prediction. I argue that these underdetermination arguments fail and depend on an implausible explication of prediction in the theory. The technical results adduced in these (...)
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  9.  2
    Daniel Kahneman & Amos Tversky (1973). On the Psychology of Prediction. Psychological Review 80 (4):237-251.
    Considers that intuitive predictions follow a judgmental heuristic-representativeness. By this heuristic, people predict the outcome that appears most representative of the evidence. Consequently, intuitive predictions are insensitive to the reliability of the evidence or to the prior probability of the outcome, in violation of the logic of statistical prediction. The hypothesis that people predict by representativeness was supported in a series of studies with both naive and sophisticated university students. The ranking of outcomes by likelihood coincided with the ranking (...)
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  10.  75
    Jennie Louise (2009). I Won't Do It! Self-Prediction, Moral Obligation and Moral Deliberation. Philosophical Studies 146 (3):327 - 348.
    This paper considers the question of whether predictions of wrongdoing are relevant to our moral obligations. After giving an analysis of ‘won’t’ claims (i.e., claims that an agent won’t Φ), the question is separated into two different issues: firstly, whether predictions of wrongdoing affect our objective moral obligations, and secondly, whether self-prediction of wrongdoing can be legitimately used in moral deliberation. I argue for an affirmative answer to both questions, although there are conditions that must be met for self- (...) to be appropriate in deliberation. The discussion illuminates an interesting and significant tension between agency and prediction. (shrink)
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  11. Kristin Andrews (2003). Knowing Mental States: The Asymmetry of Psychological Prediction and Explanation. In Quentin Smith & Aleksandar Jokic (eds.), Consciousness: New Philosophical Perspectives. Oxford University Press
    Perhaps because both explanation and prediction are key components to understanding, philosophers and psychologists often portray these two abilities as though they arise from the same competence, and sometimes they are taken to be the same competence. When explanation and prediction are associated in this way, they are taken to be two expressions of a single cognitive capacity that differ from one another only pragmatically. If the difference between prediction and explanation of human behavior is merely pragmatic, (...)
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  12.  11
    Alkistis Elliott-Graves (2016). The Problem of Prediction in Invasion Biology. Biology and Philosophy 31 (3):373-393.
    Invasion biology is a relatively young discipline which is important, interesting and currently in turmoil. Biological invaders can threaten native ecosystems and global biodiversity; they can incur massive economic costs and even introduce diseases. Invasion biologists generally agree that being able to predict when and where an invasion will occur is essential for progress in their field. However, successful predictions of this type remain elusive. This has caused a rift, as some researchers are pessimistic and believe that invasion biology has (...)
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  13.  50
    John Byron Manchak (2008). Is Prediction Possible in General Relativity? Foundations of Physics 38 (4):317-321.
    Here we briefly review the concept of "prediction" within the context of classical relativity theory. We prove a theorem asserting that one may predict one's own future only in a closed universe. We then question whether prediction is possible at all (even in closed universes). We note that interest in prediction has stemmed from considering the epistemological predicament of the observer. We argue that the definitions of prediction found thus far in the literature do not fully (...)
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  14.  13
    SteveAnthony FleetwoodHesketh (2006). Prediction in Social Science - The Case of Research on the Human Resource Management-Organisational Performance Link. [REVIEW] Journal of Critical Realism 5 (2):228-250.
    _ Source: _Volume 5, Issue 2, pp 228 - 250 Despite inroads made by critical realism against the ‘scientific method’ in social science, the latter remains strong in subject-areas like human resource management. One argument for the alleged superiority of the scientific method lies in the taken-for-granted belief that it alone can formulate empirically testable predictions. Many of those who employ the scientific method are, however, confused about the way they understand and practice prediction. This paper takes as a (...)
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  15.  33
    Michael D. Lee, Mark Steyvers, Mindy de Young & Brent Miller (2012). Inferring Expertise in Knowledge and Prediction Ranking Tasks. Topics in Cognitive Science 4 (1):151-163.
    We apply a cognitive modeling approach to the problem of measuring expertise on rank ordering problems. In these problems, people must order a set of items in terms of a given criterion (e.g., ordering American holidays through the calendar year). Using a cognitive model of behavior on this problem that allows for individual differences in knowledge, we are able to infer people's expertise directly from the rankings they provide. We show that our model-based measure of expertise outperforms self-report measures, taken (...)
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  16.  21
    Anne Springer, Simone Brandstädter & Wolfgang Prinz (2013). Dynamic Simulation and Static Matching for Action Prediction: Evidence From Body Part Priming. Cognitive Science 37 (5):936-952.
    Accurately predicting other people's actions may involve two processes: internal real-time simulation (dynamic updating) and matching recently perceived action images (static matching). Using a priming of body parts, this study aimed to differentiate the two processes. Specifically, participants played a motion-controlled video game with either their arms or legs. They then observed arm movements of a point-light actor, which were briefly occluded from view, followed by a static test pose. Participants judged whether this test pose depicted a coherent continuation of (...)
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  17.  14
    Fabian Chersi, Marcello Ferro, Giovanni Pezzulo & Vito Pirrelli (2014). Topological Self‐Organization and Prediction Learning Support Both Action and Lexical Chains in the Brain. Topics in Cognitive Science 6 (3):476-491.
    A growing body of evidence in cognitive psychology and neuroscience suggests a deep interconnection between sensory-motor and language systems in the brain. Based on recent neurophysiological findings on the anatomo-functional organization of the fronto-parietal network, we present a computational model showing that language processing may have reused or co-developed organizing principles, functionality, and learning mechanisms typical of premotor circuit. The proposed model combines principles of Hebbian topological self-organization and prediction learning. Trained on sequences of either motor or linguistic units, (...)
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  18.  1
    SteveAnthony FleetwoodHesketh (2006). Prediction in Social Science - The Case of Research on the Human Resource Management-Organisational Performance Link. Journal of Critical Realism 5 (2):228-250.
    _ Source: _Volume 5, Issue 2, pp 228 - 250 Despite inroads made by critical realism against the ‘scientific method’ in social science, the latter remains strong in subject-areas like human resource management. One argument for the alleged superiority of the scientific method lies in the taken-for-granted belief that it alone can formulate empirically testable predictions. Many of those who employ the scientific method are, however, confused about the way they understand and practice prediction. This paper takes as a (...)
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  19. Gregor Betz (2011). Prediction. In Ian Jarvie & Jesus Zamora-Bonilla (eds.), Handbook of Philosophy of Social Science. Sage
    Predictive success as an aim of science -- On the very possibility of prediction in the social sciences -- Empirical facts about social prediction: its mode, object and performance -- Understanding poor forecast performance.
     
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  20.  25
    Friedrich Stadler (2011). The Road to "Experience and Prediction" From Within: Hans Reichenbach's Scientific Correspondence From Berlin to Istanbul. Synthese 181 (1):137 - 155.
    Ever since the first meeting of the proponents of the emerging Logical Empiricism in 1923, there existed philosophical differences as well as personal rivalries between the groups in Berlin and Vienna, headed by Hans Reichenbach and Moritz Schlick, respectively. Early theoretical tensions between Schlick and Reichenbach were caused by Reichenbach's (neo) Kantian roots (esp. his version of the relativized a priori), who himself regarded the Vienna Circle as a sort of anti-realist "positivist school"—as he described it in his Experience and (...)
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  21.  6
    Steve Fleetwood & Anthony Hesketh (2006). Prediction in Social Science. Journal of Critical Realism 5 (2):228-250.
    _ Source: _Volume 5, Issue 2, pp 228 - 250 Despite inroads made by critical realism against the ‘scientific method’ in social science, the latter remains strong in subject-areas like human resource management. One argument for the alleged superiority of the scientific method lies in the taken-for-granted belief that it alone can formulate empirically testable predictions. Many of those who employ the scientific method are, however, confused about the way they understand and practice prediction. This paper takes as a (...)
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  22.  14
    W. Garrett Mitchener (2011). A Mathematical Model of Prediction-Driven Instability: How Social Structure Can Drive Language Change. [REVIEW] Journal of Logic, Language and Information 20 (3):385-396.
    I discuss a stochastic model of language learning and change. During a syntactic change, each speaker makes use of constructions from two different idealized grammars at variable rates. The model incorporates regularization in that speakers have a slight preference for using the dominant idealized grammar. It also includes incrementation: The population is divided into two interacting generations. Children can detect correlations between age and speech. They then predict where the population’s language is moving and speak according to that prediction, (...)
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  23.  15
    Stephen D. O'Leary (1997). Apocalyptic Argument and the Anticipation of Catastrophe: The Prediction of Risk and the Risks of Prediction. [REVIEW] Argumentation 11 (3):293-313.
    This essay proposes to extend the model of apocalyptic argument developedin my recent book Arguing the Apocalypse (O‘Leary, 1994) beyond the study ofreligious discourse, by applying this model to the debate over awell-publicized earthquake prediction that caused a widespread panic in theAmerican midwest in December, 1990. The first section of the essay willsummarize the essential elements of apocalyptic argument as I have earlierdefined them; the second section will apply the model to the case of the NewMadrid, Missouri, earthquake (...), in order to demonstrate thatcertain patterns of reasoning characteristic of religious apocalyptic arepresent in the discourse over an anticipated local disaster. My ultimatepurpose is to show that predictions of global and local catastrophe mayserve as extreme cases that will illuminate the dynamics of predictiveargument in general. Thus my argument will seek to undercut Daniel Bell‘sdistinction between prophecy and prediction (Bell, 1973) by establishingthat these discourses share identifiable formal and substantivecharacteristics, and depend for their rhetorical effect on anxiety, hope,far, and excitement as modes of temporal anticipation. (shrink)
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  24.  5
    G. Bonanno (2001). Prediction in Branching Time Logic. Mathematical Logic Quarterly 47 (2):239-248.
    When we make a prediction we select, among the conceivable future descriptions of the world, those that appear to us to be most plausible. We capture this by means of two binary relations, ≺c and ≺p: if t1 and t2 are points in time, we interpret t1 ≺ct2 as sayingthat t2 is in the conceivable future of t1, while t1 ≺pt2 is interpreted to mean that t2 isin the predicted future of t1. Within a branching-time framework we propose the (...)
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  25.  1
    Idil Boran (2004). Le Conséquentialisme Et le Problème de Prédiction. Archives de Philosophie du Droit 48:305-313.
    Le présent article examine une objection contre le conséquentialisme provenant de ce que l’on peut appeler « le problème de prédiction ». Le conséquentialisme nous demande de choisir l’action qui apporte la meilleure conséquence. Or, il n’est pas toujours facile, ou même possible, de prédire le futur et de savoir quelles seront exactement les conséquences de nos actions. Il n’est pas raisonnable d’attendre l’action juste de l’agent moral si le critère de justice requiert de celui-ci une prédiction qu’il n’est pas (...)
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  26.  27
    Natalie Sebanz & Guenther Knoblich (2009). Prediction in Joint Action: What, When, and Where. Topics in Cognitive Science 1 (2):353-367.
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  27.  55
    L. Jonathan Cohen (1979). On the Psychology of Prediction: Whose is the Fallacy? Cognition 7 (December):385-407.
  28.  9
    Gerry T. M. Altmann & Jelena Mirković (2009). Incrementality and Prediction in Human Sentence Processing. Cognitive Science 33 (4):583-609.
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  29.  8
    Jennifer B. Misyak, Morten H. Christiansen & J. Bruce Tomblin (2010). Sequential Expectations: The Role of Prediction‐Based Learning in Language. Topics in Cognitive Science 2 (1):138-153.
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  30.  88
    Przemysław Nowakowski (2015). Delusions: Between Phenomenology and Prediction. Avant: Trends in Interdisciplinary Studies (3/2014):11-16.
    One of the leading and central figures in research on delusions, Max Coltheart, presents and summarises his heretofore work in a short text. Miyazono and Bortolotti present an interesting argument aimed at the charges against the doxastic concept of delusions. Adams, Brown and Friston showcase a predictive-Bayesian concept of delusions. Young criticizes the current changes in the two-factor account of delusions and argues that the role of experience should not be dismissed within it. Kapusta presents an interesting, phenomenological approach to (...)
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  31.  3
    Jeremy R. Reynolds, Jeffrey M. Zacks & Todd S. Braver (2007). A Computational Model of Event Segmentation From Perceptual Prediction. Cognitive Science 31 (4):613-643.
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  32.  24
    Kengo Miyazono, Lisa Bortolotti & Matthew Broome (2015). Prediction-Error and Two-Factor Theories of Delusion Formation: Competitors or Allies? In Niall Galbraith (ed.), Aberrant Beliefs and Reasoning. Psychology Press 34-54.
  33.  59
    Gregor Betz (2010). What’s the Worst Case? The Methodology of Possibilistic Prediction. Analyse & Kritik 32 (1):87-106.
    Frank Knight (1921) famously distinguished the epistemic modes of certainty, risk, and uncertainty in order to characterize situations where deterministic, probabilistic or possibilistic foreknowledge is available. Because our probabilistic knowledge is limited, i.e. because many systems, e.g. the global climate, cannot be described and predicted probabilistically in a reliable way, Knight's third category, possibilistic foreknowledge, is not simply swept by the probabilistic mode. This raises the question how to justify possibilistic predictionsincluding the identication of the worst case. The development of (...)
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  34.  13
    Diyi Chen & Wenting Han (2013). Prediction of Multivariate Chaotic Time Series Via Radial Basis Function Neural Network. Complexity 18 (4):55-66.
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  35.  20
    Petter Næss (2004). Prediction, Regressions and Critical Realism. Journal of Critical Realism 3 (1):133-164.
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  36.  19
    Gregor Betz (2006). Prediction or Prophecy? The Boundaries of Economic Foreknowledge and Their Socio-Political Consequences. DUV.
    Gregor Betz explores the following questions: Where are the limits of economics, in particular the limits of economic foreknowledge? Are macroeconomic forecasts credible predictions or mere prophecies and what would this imply for the way economic policy decisions are taken? Is rational economic decision making possible without forecasting at all?
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  37. Haskell Fain (1958). Prediction and Constraint. Mind 67 (July):366-378.
  38.  12
    Genevieve Maricle (2011). Prediction as an Impediment to Preparedness: Lessons From the US Hurricane and Earthquake Research Enterprises. Minerva 49 (1):87-111.
    No matter one’s wealth or social position, all are subject to the threats of natural hazards. Be it fire, flood, hurricane, earthquake, tornado, or drought, the reality of hazard risk is universal. In response, governments, non-profits, and the private sector all support research to study hazards. Each has a common end in mind: to increase the resilience of vulnerable communities. While this end goal is shared across hazards, the conception of how to get there can diverge considerably. The earthquake and (...)
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  39. Peter Clark (2006). Problems of Determinism: Prediction, Propensity and Probability. In Wenceslao J. González & Jesus Alcolea (eds.), Contemporary Perspectives in Philosophy and Methodology of Science. Netbiblio
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  40.  7
    Ioannis D. Katerelos & Andreas G. Koulouris (2004). Is Prediction Possible? Chaotic Behavior of Multiple Equilibria Regulation Model in Cellular Automata Topology. Complexity 10 (1):23-36.
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  41.  11
    Peter L. Derks & Marianne I. Paclisanu (1967). Simple Strategies in Binary Prediction by Children and Adults. Journal of Experimental Psychology 73 (2):278.
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  42.  48
    Carlton W. Berenda (1953). On Emergence and Prediction. Journal of Philosophy 50 (April):269-74.
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  43.  4
    Chi‐Ming Chang, Hsu‐Sung Kuo, Shu‐Hui Chang, Hong‐Jen Chang, Der‐Ming Liou, Tabar Laszlo & Tony Hsiu‐Hsi Chen (2005). Computer‐Aided Disease Prediction System: Development of Application Software with SAS Component Language. Journal of Evaluation in Clinical Practice 11 (2):139-159.
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  44.  12
    Spencer Phillips Hey (2015). Ethics and Epistemology of Accurate Prediction in Clinical Research. Journal of Medical Ethics 41 (7):559-562.
    All major research ethics policies assert that the ethical review of clinical trial protocols should include a systematic assessment of risks and benefits. But despite this policy, protocols do not typically contain explicit probability statements about the likely risks or benefits involved in the proposed research. In this essay, I articulate a range of ethical and epistemic advantages that explicit forecasting would offer to the health research enterprise. I then consider how some particular confidence levels may come into conflict with (...)
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  45.  3
    E. Scott Geller & Charles P. Whitman (1972). Prediction Outcome and Choice Reaction Time: A Memory-Dependent Relationship. Journal of Experimental Psychology 96 (2):334.
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  46.  1
    E. Scott Geller (1974). Preceding Prediction Outcome and Prediction Outcome Probability: Interacting Determinants of Choice Reaction Time. Journal of Experimental Psychology 103 (3):426.
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  47.  1
    Jonathan Fuller, Alex Broadbent & Luis J. Flores (2015). Prediction in Epidemiology and Medicine. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 54:45-48.
  48.  6
    Tsukasa Nakamura, Osamu Takahashi, Kunihiko Matsui, Shiro Shimizu, Motoichi Setoyama, Masahisa Nakagawa, Tsuguya Fukui & Takeshi Morimoto (2006). Clinical Prediction Rules for Bacteremia and in‐Hospital Death Based on Clinical Data at the Time of Blood Withdrawal for Culture: An Evaluation of Their Development and Use. Journal of Evaluation in Clinical Practice 12 (6):692-703.
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    Max S. Schoeffler (1962). Prediction of Some Stochastic Events: A Regret Equalization Model. Journal of Experimental Psychology 64 (6):615.
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  50.  1
    E. Scott Geller & Gordon F. Pitz (1970). Effects of Prediction, Probability, and Run Length on Choice Reaction Speed. Journal of Experimental Psychology 84 (2):361.
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