The Experts below are selected from a list of 5157 Experts worldwide ranked by ideXlab platform
Bjorn Brunnander - One of the best experts on this subject based on the ideXlab platform.
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natural selection and Multiple Realisation a closer look
International Studies in The Philosophy of Science, 2013Co-Authors: Bjorn BrunnanderAbstract:The target of this paper is the claim that natural selection accounts for the Multiple Realisation of biological and psychological kinds. I argue that the explanation actually offered doesn’t provi ...
Tuomas K Pernu - One of the best experts on this subject based on the ideXlab platform.
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elimination not reduction lessons from the research domain criteria rdoc and Multiple Realisation
Behavioral and Brain Sciences, 2019Co-Authors: Tuomas K PernuAbstract:The thesis of Multiple Realisation that Borsboom et al. are relying on should not be taken for granted. In dissolving the apparent Multiple Realisation, the reductionist research strategies in psychopathology research (the Research Domain Criteria [RDoC] framework, in particular) are bound to lead to eliminativism rather than reductionism. Therefore, Borsboom et al. seem to be aiming at a wrong target.
Alexander Franklin - One of the best experts on this subject based on the ideXlab platform.
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can Multiple Realisation be explained
Philosophy, 2021Co-Authors: Alexander FranklinAbstract:Multiple Realisation prompts the question: how is it that Multiple systems all exhibit the same phenomena despite their different underlying properties? In this paper I develop a framework for addressing that question and argue that Multiple Realisation can be reductively explained. I illustrate this position by applying the framework to a simple example – the Multiple Realisation of electrical conductivity. I defend my account by addressing potential objections: contra (e.g.) Polger and Shapiro (2016), Batterman (2018), and Sober (1999), I claim that Multiple Realisation is commonplace, that it can be reductively explained, but that it requires a sui generis reductive explanatory strategy.
I G Milne - One of the best experts on this subject based on the ideXlab platform.
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a Multiple Realisation approach to managing uncertainty in the north rankin gas condensate field western australia
SPE Asia Pacific Oil and Gas Conference and Exhibition, 1998Co-Authors: S K Twartz, F Gorjy, I G MilneAbstract:A Multiple Realisation approach was used in the management of ultimate recovery uncertainty of the North Rankin gas condensate field. The aim of this approach was to identify the key uncertainties that impact ultimate recovery, reflect those uncertainties in discrete Realisations as represented on a Realisation tree, use the discrete Realisations to improve the quality of development decisions, and to evaluate the uncertainty on field ultimate recovery. Emphasis was placed on the use of production data, primarily pressure and TDT data, to reduce the range of possible Realisations, assign probabilities to Realisations and hence reduce the ultimate recovery uncertainty. This paper provides a clear and practical process for management of uncertainties from the probabilistic and deterministic perspective. The process is comprehensive and covers all steps leading to final reporting of field ultimate recovery. The steps in the process are clearly demonstrated by actual examples from the North Rankin study.
S K Twartz - One of the best experts on this subject based on the ideXlab platform.
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a Multiple Realisation approach to managing uncertainty in the north rankin gas condensate field western australia
SPE Asia Pacific Oil and Gas Conference and Exhibition, 1998Co-Authors: S K Twartz, F Gorjy, I G MilneAbstract:A Multiple Realisation approach was used in the management of ultimate recovery uncertainty of the North Rankin gas condensate field. The aim of this approach was to identify the key uncertainties that impact ultimate recovery, reflect those uncertainties in discrete Realisations as represented on a Realisation tree, use the discrete Realisations to improve the quality of development decisions, and to evaluate the uncertainty on field ultimate recovery. Emphasis was placed on the use of production data, primarily pressure and TDT data, to reduce the range of possible Realisations, assign probabilities to Realisations and hence reduce the ultimate recovery uncertainty. This paper provides a clear and practical process for management of uncertainties from the probabilistic and deterministic perspective. The process is comprehensive and covers all steps leading to final reporting of field ultimate recovery. The steps in the process are clearly demonstrated by actual examples from the North Rankin study.
