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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
https://doi.org/10.1007/978-94...
Part of book or chapter of book . 1979 . Peer-reviewed
License: Springer Nature TDM
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Suppes on the Logic of Clinical Judgment

Authors: Martin E. Lean;

Suppes on the Logic of Clinical Judgment

Abstract

Those knowledgeable about the subject of Professor Suppes’ paper will appreciate that there are few contemporary philosophers who are equal to debate with him on this topic or to criticize his application of the various probability approaches to specific domains of empirical investigation and practice. In his present paper it is mainly in the appendix, in which he sketches his calculus for determining upper and lower probability approximations, as detailed in his 1974 paper on ‘The Measurement of Belief’ [1], that Suppes exhibits his special technical expertise. There he sets forth his version of Bayes’ well-known theorem as a more plausible approach than other probability techniques for purposes of applying statistical methods to situations of practical belief, decision and practice. As is to be expected, his exposition provides no opportunity for critical comment.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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